Coursera - Machine Learning Specialization

Creation Time	Sept. 4, 2024, 11:22 p.m.
Last Access Time	April 15, 2025, 2:01 p.m.
File Size	3.5 GB
Keywords	Machine - Coursera Specialization Learning
Total Requests	248
Total Files	463
Magnet Link	Please wait ...
	Download (Magnet Link) Play (Watch Online)

advanced-learning-algorithms/04_decision-trees/05_conversations-with-andrew-optional/01_andrew-ng-and-chris-manning-on-natural-language-processing.mp4 236.2 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/06_conversations-with-andrew-optional/01_andrew-ng-and-chelsea-finn-on-ai-and-robotics.mp4 230.7 MB
machine-learning/03_week-3-classification/06_conversations-with-andrew-optional/01_andrew-ng-and-fei-fei-li-on-human-centered-ai.mp4 214.7 MB
advanced-learning-algorithms/02_neural-network-training/05_back-propagation-optional/01_what-is-a-derivative-optional.mp4 38.3 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/02_recommender-systems-implementation-detail/02_tensorflow-implementation-of-collaborative-filtering.mp4 35.9 MB
machine-learning/01_week-1-introduction-to-machine-learning/01_overview-of-machine-learning/02_applications-of-machine-learning.mp4 33.4 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/03_adding-data.mp4 32.9 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/03_learning-the-state-value-function.mp4 31.1 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/03_collaborative-filtering-algorithm.mp4 31.0 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/01_what-is-reinforcement-learning.mp4 31.0 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/06_choosing-what-features-to-use.mp4 30.9 MB
advanced-learning-algorithms/02_neural-network-training/05_back-propagation-optional/02_computation-graph-optional.mp4 30.0 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/03_model-selection-and-training-cross-validation-test-sets.mp4 29.6 MB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/04_cost-function-intuition.mp4 29.6 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/04_optimization-objective.mp4 29.5 MB
advanced-learning-algorithms/04_decision-trees/01_decision-trees/02_learning-process.mp4 29.0 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/03_the-return-in-reinforcement-learning.mp4 29.0 MB
advanced-learning-algorithms/01_neural-networks/05_speculations-on-artificial-general-intelligence-agi/01_is-there-a-path-to-agi.mp4 28.1 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/05_deciding-what-to-try-next-revisited.mp4 28.0 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/04_principal-component-analysis/02_pca-algorithm-optional.mp4 28.0 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/01_example-of-continuous-state-space-applications.mp4 27.0 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/06_bias-variance-and-neural-networks.mp4 26.9 MB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/02_neurons-and-the-brain.mp4 26.9 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/04_principal-component-analysis/01_reducing-the-number-of-features-optional.mp4 26.7 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/03_bellman-equation.mp4 26.7 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/01_finding-unusual-events.mp4 26.3 MB
advanced-learning-algorithms/02_neural-network-training/05_back-propagation-optional/03_larger-neural-network-example-optional.mp4 26.1 MB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/01_what-is-machine-learning.mp4 26.0 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/06_algorithm-refinement-mini-batch-and-soft-updates-optional.mp4 25.6 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/06_fairness-bias-and-ethics.mp4 25.3 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/05_algorithm-refinement-greedy-policy.mp4 25.3 MB
advanced-learning-algorithms/01_neural-networks/03_tensorflow-implementation/02_data-in-tensorflow.mp4 24.8 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/04_ethical-use-of-recommender-systems.mp4 24.8 MB
machine-learning/03_week-3-classification/02_cost-function-for-logistic-regression/01_cost-function-for-logistic-regression.mp4 24.6 MB
advanced-learning-algorithms/01_neural-networks/03_tensorflow-implementation/03_building-a-neural-network.mp4 24.4 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/02_deep-learning-for-content-based-filtering.mp4 24.3 MB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/03_demand-prediction.mp4 24.2 MB
advanced-learning-algorithms/02_neural-network-training/01_neural-network-training/02_training-details.mp4 24.1 MB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/01_the-problem-of-overfitting.mp4 24.0 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/04_developing-and-evaluating-an-anomaly-detection-system.mp4 23.9 MB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/02_choosing-a-split-information-gain.mp4 23.8 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/02_using-per-item-features.mp4 23.5 MB
advanced-learning-algorithms/02_neural-network-training/02_activation-functions/02_choosing-activation-functions.mp4 23.4 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/04_learning-curves.mp4 23.3 MB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/06_polynomial-regression.mp4 22.8 MB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/01_gradient-descent.mp4 22.5 MB
machine-learning/01_week-1-introduction-to-machine-learning/01_overview-of-machine-learning/01_welcome-to-machine-learning.mp4 22.2 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/04_skewed-datasets-optional/02_trading-off-precision-and-recall.mp4 22.2 MB
machine-learning/03_week-3-classification/01_classification-with-logistic-regression/02_logistic-regression.mp4 21.5 MB
advanced-learning-algorithms/01_neural-networks/04_neural-network-implementation-in-python/02_general-implementation-of-forward-propagation.mp4 21.3 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/02_regularization-and-bias-variance.mp4 21.1 MB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/04_xgboost.mp4 21.1 MB
machine-learning/03_week-3-classification/01_classification-with-logistic-regression/01_motivations.mp4 21.0 MB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/02_implementing-gradient-descent.mp4 20.9 MB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/05_regularized-logistic-regression.mp4 20.9 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/02_gaussian-normal-distribution.mp4 20.9 MB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/02_softmax.mp4 20.7 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/01_making-recommendations.mp4 20.4 MB
advanced-learning-algorithms/01_neural-networks/02_neural-network-model/01_neural-network-layer.mp4 20.4 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/03_anomaly-detection-algorithm.mp4 20.3 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/05_anomaly-detection-vs-supervised-learning.mp4 20.3 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/01_diagnosing-bias-and-variance.mp4 20.3 MB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/01_linear-regression-model-part-1.mp4 20.3 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/01_collaborative-filtering-vs-content-based-filtering.mp4 20.0 MB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/06_jupyter-notebooks.mp4 19.9 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/01_state-action-value-function-definition.mp4 19.8 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/04_binary-labels-favs-likes-and-clicks.mp4 19.8 MB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/04_regularized-linear-regression.mp4 19.8 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/03_k-means-algorithm.mp4 19.8 MB
advanced-learning-algorithms/02_neural-network-training/04_additional-neural-network-concepts/02_additional-layer-types.mp4 19.5 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/02_evaluating-a-model.mp4 19.5 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/03_establishing-a-baseline-level-of-performance.mp4 19.4 MB
machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/04_gradient-descent-for-multiple-linear-regression.mp4 19.4 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/04_random-stochastic-environment-optional.mp4 19.3 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/04_transfer-learning-using-data-from-a-different-task.mp4 19.0 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/04_skewed-datasets-optional/01_error-metrics-for-skewed-datasets.mp4 19.0 MB
machine-learning/03_week-3-classification/01_classification-with-logistic-regression/03_decision-boundary.mp4 18.9 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/02_recommender-systems-implementation-detail/01_mean-normalization.mp4 18.9 MB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/06_regression-trees-optional.mp4 18.9 MB
machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/01_multiple-features.mp4 18.9 MB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/04_unsupervised-learning-part-1.mp4 18.7 MB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/03_putting-it-together.mp4 18.4 MB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/06_running-gradient-descent.mp4 18.4 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/03_recommending-from-a-large-catalogue.mp4 18.0 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/05_initializing-k-means.mp4 17.8 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/04_principal-component-analysis/03_pca-in-code-optional.mp4 17.8 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/02_error-analysis.mp4 17.5 MB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/05_when-to-use-decision-trees.mp4 17.5 MB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/05_visualizing-the-cost-function.mp4 17.3 MB
machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/02_vectorization-part-1.mp4 17.3 MB
machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/03_vectorization-part-2.mp4 17.3 MB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/06_visualization-examples.mp4 17.2 MB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/03_cost-function-with-regularization.mp4 17.1 MB
advanced-learning-algorithms/01_neural-networks/02_neural-network-model/02_more-complex-neural-networks.mp4 17.0 MB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/04_learning-rate.mp4 16.9 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/06_choosing-the-number-of-clusters.mp4 16.9 MB
advanced-learning-algorithms/01_neural-networks/03_tensorflow-implementation/01_inference-in-code.mp4 16.8 MB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/03_cost-function-formula.mp4 16.7 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/02_recommender-systems-implementation-detail/03_finding-related-items.mp4 16.6 MB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/05_gradient-descent-for-linear-regression.mp4 16.4 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/05_full-cycle-of-a-machine-learning-project.mp4 16.4 MB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/04_choosing-the-learning-rate.mp4 16.3 MB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/02_linear-regression-model-part-2.mp4 16.2 MB
advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/03_matrix-multiplication-rules.mp4 16.1 MB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/01_measuring-purity.mp4 16.0 MB
advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/02_matrix-multiplication.mp4 15.9 MB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/05_continuous-valued-features.mp4 15.9 MB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/02_addressing-overfitting.mp4 15.7 MB
advanced-learning-algorithms/02_neural-network-training/04_additional-neural-network-concepts/01_advanced-optimization.mp4 15.6 MB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/04_improved-implementation-of-softmax.mp4 15.1 MB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/03_neural-network-with-softmax-output.mp4 15.0 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/01_iterative-loop-of-ml-development.mp4 14.8 MB
advanced-learning-algorithms/04_decision-trees/01_decision-trees/01_decision-tree-model.mp4 14.8 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/02_state-action-value-function-example.mp4 14.6 MB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/04_example-recognizing-images.mp4 14.6 MB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/03_supervised-learning-part-2.mp4 14.4 MB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/02_feature-scaling-part-2.mp4 14.4 MB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/02_sampling-with-replacement.mp4 14.3 MB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/04_using-one-hot-encoding-of-categorical-features.mp4 14.2 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/05_summary-and-thank-you/01_summary-and-thank-you.mp4 13.9 MB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/02_supervised-learning-part-1.mp4 13.9 MB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/01_feature-scaling-part-1.mp4 13.6 MB
advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/04_matrix-multiplication-code.mp4 13.4 MB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/03_gradient-descent-intuition.mp4 13.2 MB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/05_tensorflow-implementation-of-content-based-filtering.mp4 12.9 MB
advanced-learning-algorithms/02_neural-network-training/02_activation-functions/03_why-do-we-need-activation-functions.mp4 12.9 MB
machine-learning/03_week-3-classification/03_gradient-descent-for-logistic-regression/01_gradient-descent-implementation.mp4 12.8 MB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/03_random-forest-algorithm.mp4 12.7 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/02_mars-rover-example.mp4 12.7 MB
advanced-learning-algorithms/01_neural-networks/02_neural-network-model/03_inference-making-predictions-forward-propagation.mp4 12.6 MB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/01_using-multiple-decision-trees.mp4 12.5 MB
advanced-learning-algorithms/01_neural-networks/04_neural-network-implementation-in-python/01_forward-prop-in-a-single-layer.mp4 12.4 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/02_k-means-intuition.mp4 12.4 MB
advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/01_how-neural-networks-are-implemented-efficiently.mp4 12.2 MB
advanced-learning-algorithms/02_neural-network-training/02_activation-functions/01_alternatives-to-the-sigmoid-activation.mp4 12.0 MB
machine-learning/03_week-3-classification/02_cost-function-for-logistic-regression/02_simplified-cost-function-for-logistic-regression.mp4 11.7 MB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/01_deciding-what-to-try-next.mp4 11.4 MB
advanced-learning-algorithms/02_neural-network-training/01_neural-network-training/01_tensorflow-implementation.mp4 11.4 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/05_review-of-key-concepts.mp4 11.4 MB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/05_classification-with-multiple-outputs-optional.mp4 11.3 MB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/03_checking-gradient-descent-for-convergence.mp4 11.0 MB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/01_welcome.mp4 10.6 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/02_lunar-lander.mp4 10.4 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/01_what-is-clustering.mp4 8.8 MB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/01_multiclass.mp4 8.4 MB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/01_welcome-to-the-course/01_welcome.mp4 8.3 MB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/05_unsupervised-learning-part-2.mp4 8.2 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/07_the-state-of-reinforcement-learning.mp4 7.9 MB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/05_feature-engineering.mp4 7.8 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/04_algorithm-refinement-improved-neural-network-architecture.mp4 7.8 MB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/04_making-decisions-policies-in-reinforcement-learning.mp4 5.8 MB
advanced-learning-algorithms/04_decision-trees/05_conversations-with-andrew-optional/01_andrew-ng-and-chris-manning-on-natural-language-processing.en.srt 63.9 KB
machine-learning/03_week-3-classification/06_conversations-with-andrew-optional/01_andrew-ng-and-fei-fei-li-on-human-centered-ai.en.srt 59.7 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/06_conversations-with-andrew-optional/01_andrew-ng-and-chelsea-finn-on-ai-and-robotics.en.srt 50.6 KB
advanced-learning-algorithms/04_decision-trees/05_conversations-with-andrew-optional/01_andrew-ng-and-chris-manning-on-natural-language-processing.en.txt 39.8 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/06_conversations-with-andrew-optional/01_andrew-ng-and-chelsea-finn-on-ai-and-robotics.en.txt 31.8 KB
machine-learning/03_week-3-classification/06_conversations-with-andrew-optional/01_andrew-ng-and-fei-fei-li-on-human-centered-ai.en.txt 30.7 KB
advanced-learning-algorithms/02_neural-network-training/05_back-propagation-optional/01_what-is-a-derivative-optional.en.srt 29.7 KB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/03_demand-prediction.en.srt 26.6 KB
advanced-learning-algorithms/02_neural-network-training/05_back-propagation-optional/02_computation-graph-optional.en.srt 26.4 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/03_learning-the-state-value-function.en.srt 25.2 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/04_principal-component-analysis/02_pca-algorithm-optional.en.srt 24.4 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/03_model-selection-and-training-cross-validation-test-sets.en.srt 21.3 KB
advanced-learning-algorithms/02_neural-network-training/01_neural-network-training/02_training-details.en.srt 20.9 KB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/04_cost-function-intuition.en.srt 20.2 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/04_transfer-learning-using-data-from-a-different-task.en.srt 20.2 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/04_learning-curves.en.srt 20.1 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/03_adding-data.en.srt 18.9 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/03_collaborative-filtering-algorithm.en.srt 18.8 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/06_choosing-what-features-to-use.en.srt 18.6 KB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/01_the-problem-of-overfitting.en.srt 18.3 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/04_skewed-datasets-optional/02_trading-off-precision-and-recall.en.srt 18.3 KB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/02_neurons-and-the-brain.en.srt 18.3 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/04_principal-component-analysis/01_reducing-the-number-of-features-optional.en.srt 18.1 KB
advanced-learning-algorithms/04_decision-trees/01_decision-trees/02_learning-process.en.srt 18.0 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/01_diagnosing-bias-and-variance.en.srt 17.8 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/03_bellman-equation.en.srt 17.7 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/06_algorithm-refinement-mini-batch-and-soft-updates-optional.en.srt 17.7 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/04_developing-and-evaluating-an-anomaly-detection-system.en.srt 17.5 KB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/02_choosing-a-split-information-gain.en.srt 17.4 KB
machine-learning/03_week-3-classification/02_cost-function-for-logistic-regression/01_cost-function-for-logistic-regression.en.srt 17.1 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/04_skewed-datasets-optional/01_error-metrics-for-skewed-datasets.en.srt 17.0 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/04_ethical-use-of-recommender-systems.en.srt 16.9 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/04_principal-component-analysis/03_pca-in-code-optional.en.srt 16.7 KB
advanced-learning-algorithms/01_neural-networks/05_speculations-on-artificial-general-intelligence-agi/01_is-there-a-path-to-agi.en.srt 16.4 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/02_regularization-and-bias-variance.en.srt 16.3 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/03_establishing-a-baseline-level-of-performance.en.srt 15.8 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/03_the-return-in-reinforcement-learning.en.srt 15.7 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/02_recommender-systems-implementation-detail/02_tensorflow-implementation-of-collaborative-filtering.en.srt 15.5 KB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/02_softmax.en.srt 15.4 KB
advanced-learning-algorithms/02_neural-network-training/05_back-propagation-optional/01_what-is-a-derivative-optional.en.txt 15.2 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/02_gaussian-normal-distribution.en.srt 15.0 KB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/01_linear-regression-model-part-1.en.srt 14.8 KB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/03_putting-it-together.en.srt 14.6 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/06_bias-variance-and-neural-networks.en.srt 14.6 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/01_finding-unusual-events.en.srt 14.5 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/05_full-cycle-of-a-machine-learning-project.en.srt 14.5 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/05_deciding-what-to-try-next-revisited.en.srt 14.5 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/01_collaborative-filtering-vs-content-based-filtering.en.srt 14.3 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/03_k-means-algorithm.en.srt 14.2 KB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/02_implementing-gradient-descent.en.srt 14.2 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/05_algorithm-refinement-greedy-policy.en.srt 14.2 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/02_deep-learning-for-content-based-filtering.en.srt 14.2 KB
machine-learning/03_week-3-classification/01_classification-with-logistic-regression/03_decision-boundary.en.srt 14.1 KB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/03_demand-prediction.en.txt 14.0 KB
advanced-learning-algorithms/02_neural-network-training/02_activation-functions/02_choosing-activation-functions.en.srt 13.8 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/04_optimization-objective.en.srt 13.7 KB
advanced-learning-algorithms/02_neural-network-training/05_back-propagation-optional/02_computation-graph-optional.en.txt 13.6 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/01_state-action-value-function-definition.en.srt 13.6 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/01_multiple-features.en.srt 13.4 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/06_fairness-bias-and-ethics.en.srt 13.4 KB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/04_improved-implementation-of-softmax.en.srt 13.4 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/03_anomaly-detection-algorithm.en.srt 13.3 KB
machine-learning/03_week-3-classification/01_classification-with-logistic-regression/02_logistic-regression.en.srt 13.3 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/02_error-analysis.en.srt 13.2 KB
advanced-learning-algorithms/01_neural-networks/03_tensorflow-implementation/02_data-in-tensorflow.en.srt 13.2 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/04_random-stochastic-environment-optional.en.srt 13.1 KB
advanced-learning-algorithms/01_neural-networks/02_neural-network-model/01_neural-network-layer.en.srt 13.0 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/03_learning-the-state-value-function.en.txt 12.9 KB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/02_addressing-overfitting.en.srt 12.9 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/02_evaluating-a-model.en.srt 12.8 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/04_principal-component-analysis/02_pca-algorithm-optional.en.txt 12.8 KB
machine-learning/03_week-3-classification/01_classification-with-logistic-regression/01_motivations.en.srt 12.7 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/02_using-per-item-features.en.srt 12.7 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/01_what-is-reinforcement-learning.en.srt 12.5 KB
advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/02_matrix-multiplication.en.srt 12.3 KB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/05_visualizing-the-cost-function.en.srt 12.3 KB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/01_gradient-descent.en.srt 12.2 KB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/06_regression-trees-optional.en.srt 12.2 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/01_iterative-loop-of-ml-development.en.srt 12.1 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/03_adding-data.en.txt 12.0 KB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/04_regularized-linear-regression.en.srt 12.0 KB
advanced-learning-algorithms/02_neural-network-training/05_back-propagation-optional/03_larger-neural-network-example-optional.en.srt 11.9 KB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/03_cost-function-formula.en.srt 11.9 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/06_choosing-what-features-to-use.en.txt 11.9 KB
advanced-learning-algorithms/01_neural-networks/02_neural-network-model/02_more-complex-neural-networks.en.srt 11.7 KB
advanced-learning-algorithms/01_neural-networks/04_neural-network-implementation-in-python/02_general-implementation-of-forward-propagation.en.srt 11.6 KB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/04_unsupervised-learning-part-1.en.srt 11.6 KB
advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/03_matrix-multiplication-rules.en.srt 11.4 KB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/03_cost-function-with-regularization.en.srt 11.3 KB
advanced-learning-algorithms/02_neural-network-training/04_additional-neural-network-concepts/02_additional-layer-types.en.srt 11.3 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/03_model-selection-and-training-cross-validation-test-sets.en.txt 11.2 KB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/04_learning-rate.en.srt 11.2 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/05_anomaly-detection-vs-supervised-learning.en.srt 11.2 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/06_choosing-the-number-of-clusters.en.srt 11.2 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/04_gradient-descent-for-multiple-linear-regression.en.srt 11.1 KB
advanced-learning-algorithms/02_neural-network-training/01_neural-network-training/02_training-details.en.txt 10.9 KB
advanced-learning-algorithms/04_decision-trees/01_decision-trees/01_decision-tree-model.en.srt 10.8 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/02_feature-scaling-part-2.en.srt 10.8 KB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/02_supervised-learning-part-1.en.srt 10.8 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/02_recommender-systems-implementation-detail/01_mean-normalization.en.srt 10.7 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/05_initializing-k-means.en.srt 10.7 KB
advanced-learning-algorithms/01_neural-networks/03_tensorflow-implementation/03_building-a-neural-network.en.srt 10.7 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/04_binary-labels-favs-likes-and-clicks.en.srt 10.6 KB
advanced-learning-algorithms/02_neural-network-training/04_additional-neural-network-concepts/01_advanced-optimization.en.srt 10.5 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/04_transfer-learning-using-data-from-a-different-task.en.txt 10.5 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/04_learning-curves.en.txt 10.5 KB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/05_when-to-use-decision-trees.en.srt 10.5 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/02_mars-rover-example.en.srt 10.3 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/02_recommender-systems-implementation-detail/03_finding-related-items.en.srt 10.2 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/03_recommending-from-a-large-catalogue.en.srt 10.2 KB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/04_example-recognizing-images.en.srt 10.2 KB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/01_measuring-purity.en.srt 10.2 KB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/04_cost-function-intuition.en.txt 10.2 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/03_vectorization-part-2.en.srt 10.0 KB
advanced-learning-algorithms/01_neural-networks/03_tensorflow-implementation/01_inference-in-code.en.srt 10.0 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/03_collaborative-filtering-algorithm.en.txt 10.0 KB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/03_gradient-descent-intuition.en.srt 10.0 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/02_vectorization-part-1.en.srt 9.7 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/01_example-of-continuous-state-space-applications.en.srt 9.7 KB
machine-learning/03_week-3-classification/03_gradient-descent-for-logistic-regression/01_gradient-descent-implementation.en.srt 9.6 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/04_choosing-the-learning-rate.en.srt 9.6 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/02_recommender-systems-implementation-detail/02_tensorflow-implementation-of-collaborative-filtering.en.txt 9.6 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/04_skewed-datasets-optional/02_trading-off-precision-and-recall.en.txt 9.6 KB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/01_the-problem-of-overfitting.en.txt 9.6 KB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/02_linear-regression-model-part-2.en.srt 9.6 KB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/02_neurons-and-the-brain.en.txt 9.5 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/06_bias-variance-and-neural-networks.en.txt 9.5 KB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/01_what-is-machine-learning.en.srt 9.5 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/06_algorithm-refinement-mini-batch-and-soft-updates-optional.en.txt 9.4 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/06_polynomial-regression.en.srt 9.4 KB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/04_xgboost.en.srt 9.4 KB
advanced-learning-algorithms/04_decision-trees/01_decision-trees/02_learning-process.en.txt 9.4 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/01_finding-unusual-events.en.txt 9.4 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/04_principal-component-analysis/01_reducing-the-number-of-features-optional.en.txt 9.4 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/01_diagnosing-bias-and-variance.en.txt 9.2 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/04_developing-and-evaluating-an-anomaly-detection-system.en.txt 9.2 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/03_bellman-equation.en.txt 9.2 KB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/03_neural-network-with-softmax-output.en.srt 9.1 KB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/05_gradient-descent-for-linear-regression.en.srt 9.1 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/02_k-means-intuition.en.srt 9.0 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/04_ethical-use-of-recommender-systems.en.txt 9.0 KB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/02_choosing-a-split-information-gain.en.txt 9.0 KB
machine-learning/03_week-3-classification/02_cost-function-for-logistic-regression/01_cost-function-for-logistic-regression.en.txt 8.9 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/04_skewed-datasets-optional/01_error-metrics-for-skewed-datasets.en.txt 8.9 KB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/03_supervised-learning-part-2.en.srt 8.9 KB
advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/04_matrix-multiplication-code.en.srt 8.8 KB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/03_random-forest-algorithm.en.srt 8.8 KB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/06_visualization-examples.en.srt 8.7 KB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/05_regularized-logistic-regression.en.srt 8.7 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/04_optimization-objective.en.txt 8.6 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/04_principal-component-analysis/03_pca-in-code-optional.en.txt 8.6 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/06_fairness-bias-and-ethics.en.txt 8.6 KB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/05_continuous-valued-features.en.srt 8.6 KB
advanced-learning-algorithms/01_neural-networks/05_speculations-on-artificial-general-intelligence-agi/01_is-there-a-path-to-agi.en.txt 8.6 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/05_review-of-key-concepts.en.srt 8.5 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/03_anomaly-detection-algorithm.en.txt 8.4 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/01_state-action-value-function-definition.en.txt 8.3 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/03_checking-gradient-descent-for-convergence.en.srt 8.3 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/02_regularization-and-bias-variance.en.txt 8.3 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/03_establishing-a-baseline-level-of-performance.en.txt 8.3 KB
advanced-learning-algorithms/01_neural-networks/03_tensorflow-implementation/02_data-in-tensorflow.en.txt 8.3 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/03_the-return-in-reinforcement-learning.en.txt 8.2 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/02_evaluating-a-model.en.txt 8.2 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/01_what-is-reinforcement-learning.en.txt 8.0 KB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/02_softmax.en.txt 7.9 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/02_gaussian-normal-distribution.en.txt 7.9 KB
machine-learning/03_week-3-classification/01_classification-with-logistic-regression/01_motivations.en.txt 7.8 KB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/03_putting-it-together.en.txt 7.8 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/02_using-per-item-features.en.txt 7.8 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/02_lunar-lander.en.srt 7.8 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/02_bias-and-variance/05_deciding-what-to-try-next-revisited.en.txt 7.8 KB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/06_regression-trees-optional.en.txt 7.7 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/05_full-cycle-of-a-machine-learning-project.en.txt 7.7 KB
machine-learning/03_week-3-classification/02_cost-function-for-logistic-regression/02_simplified-cost-function-for-logistic-regression.en.srt 7.6 KB
advanced-learning-algorithms/02_neural-network-training/02_activation-functions/03_why-do-we-need-activation-functions.en.srt 7.6 KB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/01_linear-regression-model-part-1.en.txt 7.6 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/01_feature-scaling-part-1.en.srt 7.6 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/05_algorithm-refinement-greedy-policy.en.txt 7.5 KB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/02_implementing-gradient-descent.en.txt 7.5 KB
machine-learning/01_week-1-introduction-to-machine-learning/01_overview-of-machine-learning/02_applications-of-machine-learning.en.srt 7.5 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/01_collaborative-filtering-vs-content-based-filtering.en.txt 7.4 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/02_deep-learning-for-content-based-filtering.en.txt 7.4 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/03_k-means-algorithm.en.txt 7.4 KB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/04_unsupervised-learning-part-1.en.txt 7.4 KB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/06_jupyter-notebooks.en.srt 7.3 KB
advanced-learning-algorithms/02_neural-network-training/05_back-propagation-optional/03_larger-neural-network-example-optional.en.txt 7.3 KB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/06_running-gradient-descent.en.srt 7.3 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/05_tensorflow-implementation-of-content-based-filtering.en.srt 7.3 KB
machine-learning/03_week-3-classification/01_classification-with-logistic-regression/03_decision-boundary.en.txt 7.3 KB
advanced-learning-algorithms/02_neural-network-training/04_additional-neural-network-concepts/02_additional-layer-types.en.txt 7.2 KB
advanced-learning-algorithms/02_neural-network-training/02_activation-functions/02_choosing-activation-functions.en.txt 7.2 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/01_making-recommendations.en.srt 7.2 KB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/03_cost-function-with-regularization.en.txt 7.2 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/03_anomaly-detection/05_anomaly-detection-vs-supervised-learning.en.txt 7.1 KB
advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/03_matrix-multiplication-rules.en.txt 7.1 KB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/04_improved-implementation-of-softmax.en.txt 7.1 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/02_error-analysis.en.txt 7.1 KB
machine-learning/03_week-3-classification/01_classification-with-logistic-regression/02_logistic-regression.en.txt 7.0 KB
advanced-learning-algorithms/01_neural-networks/02_neural-network-model/03_inference-making-predictions-forward-propagation.en.srt 7.0 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/05_initializing-k-means.en.txt 7.0 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/01_multiple-features.en.txt 6.9 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/04_random-stochastic-environment-optional.en.txt 6.9 KB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/04_learning-rate.en.txt 6.9 KB
advanced-learning-algorithms/01_neural-networks/03_tensorflow-implementation/03_building-a-neural-network.en.txt 6.9 KB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/02_addressing-overfitting.en.txt 6.9 KB
advanced-learning-algorithms/01_neural-networks/02_neural-network-model/01_neural-network-layer.en.txt 6.8 KB
advanced-learning-algorithms/02_neural-network-training/02_activation-functions/01_alternatives-to-the-sigmoid-activation.en.srt 6.8 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/02_state-action-value-function-example.en.srt 6.8 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/01_deciding-what-to-try-next.en.srt 6.8 KB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/05_classification-with-multiple-outputs-optional.en.srt 6.8 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/02_recommender-systems-implementation-detail/01_mean-normalization.en.txt 6.7 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/04_binary-labels-favs-likes-and-clicks.en.txt 6.7 KB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/04_using-one-hot-encoding-of-categorical-features.en.srt 6.6 KB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/02_sampling-with-replacement.en.srt 6.5 KB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/01_using-multiple-decision-trees.en.srt 6.4 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/03_machine-learning-development-process/01_iterative-loop-of-ml-development.en.txt 6.4 KB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/01_gradient-descent.en.txt 6.4 KB
advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/02_matrix-multiplication.en.txt 6.4 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/03_recommending-from-a-large-catalogue.en.txt 6.4 KB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/04_regularized-linear-regression.en.txt 6.4 KB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/05_visualizing-the-cost-function.en.txt 6.3 KB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/03_cost-function-formula.en.txt 6.2 KB
advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/01_how-neural-networks-are-implemented-efficiently.en.srt 6.1 KB
advanced-learning-algorithms/01_neural-networks/02_neural-network-model/02_more-complex-neural-networks.en.txt 6.1 KB
advanced-learning-algorithms/01_neural-networks/04_neural-network-implementation-in-python/01_forward-prop-in-a-single-layer.en.srt 6.1 KB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/04_xgboost.en.txt 6.0 KB
advanced-learning-algorithms/01_neural-networks/04_neural-network-implementation-in-python/02_general-implementation-of-forward-propagation.en.txt 6.0 KB
advanced-learning-algorithms/02_neural-network-training/01_neural-network-training/01_tensorflow-implementation.en.srt 5.9 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/04_gradient-descent-for-multiple-linear-regression.en.txt 5.9 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/01_what-is-clustering.en.srt 5.9 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/06_choosing-the-number-of-clusters.en.txt 5.8 KB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/05_unsupervised-learning-part-2.en.srt 5.8 KB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/03_neural-network-with-softmax-output.en.txt 5.8 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/02_k-means-intuition.en.txt 5.7 KB
advanced-learning-algorithms/04_decision-trees/01_decision-trees/01_decision-tree-model.en.txt 5.7 KB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/02_supervised-learning-part-1.en.txt 5.6 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/02_feature-scaling-part-2.en.txt 5.6 KB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/03_random-forest-algorithm.en.txt 5.6 KB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/05_when-to-use-decision-trees.en.txt 5.6 KB
advanced-learning-algorithms/02_neural-network-training/04_additional-neural-network-concepts/01_advanced-optimization.en.txt 5.6 KB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/03_supervised-learning-part-2.en.txt 5.5 KB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/05_continuous-valued-features.en.txt 5.5 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/01_welcome-to-the-course/01_welcome.en.srt 5.5 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/02_recommender-systems-implementation-detail/03_finding-related-items.en.txt 5.4 KB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/01_measuring-purity.en.txt 5.4 KB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/01_welcome.en.srt 5.4 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/02_mars-rover-example.en.txt 5.3 KB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/04_example-recognizing-images.en.txt 5.3 KB
advanced-learning-algorithms/04_decision-trees/06_acknowledgments/01_acknowledgements_instructions.html 5.3 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/07_acknowledgments/01_acknowledgments_instructions.html 5.3 KB
machine-learning/03_week-3-classification/07_acknowledgments/01_acknowledgments_instructions.html 5.3 KB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/03_gradient-descent-intuition.en.txt 5.3 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/05_summary-and-thank-you/01_summary-and-thank-you.en.srt 5.3 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/03_vectorization-part-2.en.txt 5.3 KB
advanced-learning-algorithms/01_neural-networks/03_tensorflow-implementation/01_inference-in-code.en.txt 5.2 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/01_multiple-linear-regression/02_vectorization-part-1.en.txt 5.1 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/04_choosing-the-learning-rate.en.txt 5.1 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/01_example-of-continuous-state-space-applications.en.txt 5.0 KB
machine-learning/03_week-3-classification/03_gradient-descent-for-logistic-regression/01_gradient-descent-implementation.en.txt 5.0 KB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/02_linear-regression-model-part-2.en.txt 5.0 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/06_polynomial-regression.en.txt 5.0 KB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/01_what-is-machine-learning.en.txt 5.0 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/02_lunar-lander.en.txt 4.9 KB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/05_gradient-descent-for-linear-regression.en.txt 4.9 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/05_feature-engineering.en.srt 4.9 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/01_feature-scaling-part-1.en.txt 4.8 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/04_algorithm-refinement-improved-neural-network-architecture.en.srt 4.7 KB
machine-learning/03_week-3-classification/04_the-problem-of-overfitting/05_regularized-logistic-regression.en.txt 4.7 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/01_collaborative-filtering/01_making-recommendations.en.txt 4.6 KB
advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/04_matrix-multiplication-code.en.txt 4.6 KB
machine-learning/01_week-1-introduction-to-machine-learning/03_regression-model/06_visualization-examples.en.txt 4.6 KB
machine-learning/01_week-1-introduction-to-machine-learning/04_train-the-model-with-gradient-descent/06_running-gradient-descent.en.txt 4.6 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/05_review-of-key-concepts.en.txt 4.5 KB
advanced-learning-algorithms/01_neural-networks/02_neural-network-model/03_inference-making-predictions-forward-propagation.en.txt 4.3 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/03_checking-gradient-descent-for-convergence.en.txt 4.3 KB
advanced-learning-algorithms/04_decision-trees/02_decision-tree-learning/04_using-one-hot-encoding-of-categorical-features.en.txt 4.3 KB
advanced-learning-algorithms/02_neural-network-training/02_activation-functions/01_alternatives-to-the-sigmoid-activation.en.txt 4.3 KB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/01_multiclass.en.srt 4.3 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/02_state-action-value-function/02_state-action-value-function-example.en.txt 4.3 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/07_the-state-of-reinforcement-learning.en.srt 4.0 KB
advanced-learning-algorithms/02_neural-network-training/02_activation-functions/03_why-do-we-need-activation-functions.en.txt 4.0 KB
machine-learning/03_week-3-classification/02_cost-function-for-logistic-regression/02_simplified-cost-function-for-logistic-regression.en.txt 3.9 KB
machine-learning/01_week-1-introduction-to-machine-learning/01_overview-of-machine-learning/02_applications-of-machine-learning.en.txt 3.9 KB
machine-learning/01_week-1-introduction-to-machine-learning/01_overview-of-machine-learning/01_welcome-to-machine-learning.en.srt 3.9 KB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/06_jupyter-notebooks.en.txt 3.9 KB
unsupervised-learning-recommenders-reinforcement-learning/02_recommender-systems/03_content-based-filtering/05_tensorflow-implementation-of-content-based-filtering.en.txt 3.9 KB
advanced-learning-algorithms/01_neural-networks/04_neural-network-implementation-in-python/01_forward-prop-in-a-single-layer.en.txt 3.8 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/04_making-decisions-policies-in-reinforcement-learning.en.srt 3.7 KB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/05_classification-with-multiple-outputs-optional.en.txt 3.6 KB
advanced-learning-algorithms/03_advice-for-applying-machine-learning/01_advice-for-applying-machine-learning/01_deciding-what-to-try-next.en.txt 3.6 KB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/02_sampling-with-replacement.en.txt 3.4 KB
advanced-learning-algorithms/04_decision-trees/03_tree-ensembles/01_using-multiple-decision-trees.en.txt 3.4 KB
advanced-learning-algorithms/01_neural-networks/06_vectorization-optional/01_how-neural-networks-are-implemented-efficiently.en.txt 3.2 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/02_clustering/01_what-is-clustering.en.txt 3.2 KB
machine-learning/01_week-1-introduction-to-machine-learning/02_supervised-vs-unsupervised-machine-learning/05_unsupervised-learning-part-2.en.txt 3.1 KB
advanced-learning-algorithms/02_neural-network-training/01_neural-network-training/01_tensorflow-implementation.en.txt 3.1 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/01_welcome-to-the-course/01_welcome.en.txt 2.9 KB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/01_welcome.en.txt 2.8 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/05_summary-and-thank-you/01_summary-and-thank-you.en.txt 2.8 KB
advanced-learning-algorithms/02_neural-network-training/03_multiclass-classification/01_multiclass.en.txt 2.8 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/07_the-state-of-reinforcement-learning.en.txt 2.6 KB
machine-learning/02_week-2-regression-with-multiple-input-variables/02_gradient-descent-in-practice/05_feature-engineering.en.txt 2.5 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/03_continuous-state-spaces/04_algorithm-refinement-improved-neural-network-architecture.en.txt 2.5 KB
machine-learning/01_week-1-introduction-to-machine-learning/01_overview-of-machine-learning/01_welcome-to-machine-learning.en.txt 2.4 KB
advanced-learning-algorithms/04_decision-trees/04_end-of-access-to-lab-notebooks/01_important-reminder-about-end-of-access-to-lab-notebooks_instructions.html 2.2 KB
machine-learning/03_week-3-classification/05_end-of-access-to-lab-notebooks/01_important-reminder-about-end-of-access-to-lab-notebooks_instructions.html 2.2 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/04_end-of-access-to-lab-notebooks/01_important-reminder-about-end-of-access-to-lab-notebooks_instructions.html 2.2 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/01_reinforcement-learning-introduction/04_making-decisions-policies-in-reinforcement-learning.en.txt 2.0 KB
unsupervised-learning-recommenders-reinforcement-learning/03_reinforcement-learning/07_acknowledgments/02_optional-opportunity-to-mentor-other-learners_instructions.html 1.7 KB
advanced-learning-algorithms/01_neural-networks/01_neural-networks-intuition/05_important-have-questions-issues-or-ideas-join-our-forum_instructions.html 1.6 KB
machine-learning/01_week-1-introduction-to-machine-learning/01_overview-of-machine-learning/03_important-have-questions-issues-or-ideas-join-our-forum_instructions.html 1.6 KB
unsupervised-learning-recommenders-reinforcement-learning/01_unsupervised-learning/01_welcome-to-the-course/02_important-have-questions-issues-or-ideas-join-our-forum_instructions.html 1.6 KB

Coursera - Machine Learning Specialization

File List

Download Torrent

Related Resources

Copyright Infringement