Coursera - Applied Machine Learning in Python
File List
- 03_module-3/01_module-3-evaluation/01_model-evaluation-selection.mp4 31.8 MB
- 02_module-2/01_module-2-supervised-machine-learning/05_linear-regression-least-squares.mp4 30.3 MB
- 02_module-2/01_module-2-supervised-machine-learning/06_linear-regression-ridge-lasso-and-polynomial-regression.mp4 29.3 MB
- 02_module-2/01_module-2-supervised-machine-learning/12_decision-trees.mp4 27.5 MB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/05_neural-networks.mp4 27.1 MB
- 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/07_k-nearest-neighbors-classification.mp4 26.9 MB
- 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/03_key-concepts-in-machine-learning.mp4 23.8 MB
- 03_module-3/01_module-3-evaluation/08_model-selection-optimizing-classifiers-for-different-evaluation-metrics.mp4 20.1 MB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/08_data-leakage.mp4 19.1 MB
- 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/05_an-example-machine-learning-problem.mp4 19.1 MB
- 02_module-2/01_module-2-supervised-machine-learning/01_introduction-to-supervised-machine-learning.mp4 19.0 MB
- 02_module-2/01_module-2-supervised-machine-learning/08_linear-classifiers-support-vector-machines.mp4 18.3 MB
- 02_module-2/01_module-2-supervised-machine-learning/04_k-nearest-neighbors-classification-and-regression.mp4 17.8 MB
- 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/02_introduction.mp4 17.5 MB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/03_random-forests.mp4 17.4 MB
- 03_module-3/01_module-3-evaluation/05_multi-class-evaluation.mp4 16.7 MB
- 02_module-2/01_module-2-supervised-machine-learning/07_logistic-regression.mp4 16.5 MB
- 03_module-3/01_module-3-evaluation/02_confusion-matrices-basic-evaluation-metrics.mp4 16.2 MB
- 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/06_examining-the-data.mp4 15.7 MB
- 02_module-2/01_module-2-supervised-machine-learning/02_overfitting-and-underfitting.mp4 15.6 MB
- 02_module-2/01_module-2-supervised-machine-learning/11_cross-validation.mp4 12.9 MB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/02_naive-bayes-classifiers.mp4 12.3 MB
- 02_module-2/01_module-2-supervised-machine-learning/10_kernalized-support-vector-machines.mp4 12.2 MB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/06_deep-learning-optional.mp4 10.8 MB
- 02_module-2/01_module-2-supervised-machine-learning/09_multi-class-classification.mp4 9.9 MB
- 03_module-3/01_module-3-evaluation/03_classifier-decision-functions.mp4 9.9 MB
- 03_module-3/01_module-3-evaluation/06_regression-evaluation.mp4 9.7 MB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/04_gradient-boosted-decision-trees.mp4 8.5 MB
- 03_module-3/01_module-3-evaluation/04_precision-recall-and-roc-curves.mp4 8.1 MB
- 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/04_python-tools-for-machine-learning.mp4 7.7 MB
- 02_module-2/01_module-2-supervised-machine-learning/03_supervised-learning-datasets.mp4 7.3 MB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/01_introduction.mp4 4.6 MB
- 03_module-3/01_module-3-evaluation/07_practical-guide-to-controlled-experiments-on-the-web.pdf 493.0 KB
- 02_module-2/01_module-2-supervised-machine-learning/13_a-few-useful-things-to-know-about-machine-learning_cacm12.pdf 156.4 KB
- 03_module-3/01_module-3-evaluation/01_model-evaluation-selection.en.srt 30.1 KB
- 02_module-2/01_module-2-supervised-machine-learning/12_decision-trees.en.srt 28.4 KB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/05_neural-networks.en.srt 27.9 KB
- 02_module-2/01_module-2-supervised-machine-learning/05_linear-regression-least-squares.en.srt 27.5 KB
- 02_module-2/01_module-2-supervised-machine-learning/06_linear-regression-ridge-lasso-and-polynomial-regression.en.srt 27.2 KB
- 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/07_k-nearest-neighbors-classification.en.srt 26.2 KB
- 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/03_key-concepts-in-machine-learning.en.srt 18.8 KB
- 03_module-3/01_module-3-evaluation/08_model-selection-optimizing-classifiers-for-different-evaluation-metrics.en.srt 17.9 KB
- 02_module-2/01_module-2-supervised-machine-learning/07_logistic-regression.en.srt 17.1 KB
- 02_module-2/01_module-2-supervised-machine-learning/04_k-nearest-neighbors-classification-and-regression.en.srt 17.1 KB
- 02_module-2/01_module-2-supervised-machine-learning/01_introduction-to-supervised-machine-learning.en.srt 17.1 KB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/03_random-forests.en.srt 17.1 KB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/08_data-leakage.en.srt 16.7 KB
- 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/02_introduction.en.srt 16.1 KB
- 03_module-3/01_module-3-evaluation/02_confusion-matrices-basic-evaluation-metrics.en.srt 15.8 KB
- 02_module-2/01_module-2-supervised-machine-learning/02_overfitting-and-underfitting.en.srt 15.8 KB
- 02_module-2/01_module-2-supervised-machine-learning/08_linear-classifiers-support-vector-machines.en.srt 15.5 KB
- 03_module-3/01_module-3-evaluation/05_multi-class-evaluation.en.srt 15.2 KB
- 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/05_an-example-machine-learning-problem.en.srt 14.8 KB
- 02_module-2/01_module-2-supervised-machine-learning/11_cross-validation.en.srt 13.0 KB
- 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/06_examining-the-data.en.srt 12.1 KB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/02_naive-bayes-classifiers.en.srt 11.2 KB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/06_deep-learning-optional.en.srt 10.3 KB
- 02_module-2/01_module-2-supervised-machine-learning/10_kernalized-support-vector-machines.en.srt 9.9 KB
- 03_module-3/01_module-3-evaluation/03_classifier-decision-functions.en.srt 9.0 KB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/04_gradient-boosted-decision-trees.en.srt 8.4 KB
- 02_module-2/01_module-2-supervised-machine-learning/09_multi-class-classification.en.srt 8.3 KB
- 03_module-3/01_module-3-evaluation/06_regression-evaluation.en.srt 7.8 KB
- 03_module-3/01_module-3-evaluation/04_precision-recall-and-roc-curves.en.srt 7.5 KB
- 02_module-2/01_module-2-supervised-machine-learning/03_supervised-learning-datasets.en.srt 6.7 KB
- 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/04_python-tools-for-machine-learning.en.srt 6.1 KB
- 04_module-4/01_module-4-supervised-machine-learning-part-2/01_introduction.en.srt 4.6 KB
- Sites you may like!/Join Us - HAX4EVER.txt 177 bytes
- Sites you may like!/TGX - Torrent Galaxy.url 115 bytes
- Sites you may like!/OG - 1337X.TO.url 112 bytes
- Sites you may like!/APKSOUP - Premium Apps!.url 110 bytes
Download Torrent
Related Resources
Copyright Infringement
If the content above is not authorized, please contact us via anywarmservice[AT]gmail.com. Remember to include the full url in your complaint.