Building Machine Learning Systems with TensorFlow [Video]
File List
- Code/Section 8/imagenet-vgg-verydeep-19.mat 549.4 MB
- 7.5-Writing Music a la Bach - Building Machine Learning Systems with TensorFlow [Video].mp4 30.4 MB
- 1.4-Basic Tensor Methods - Building Machine Learning Systems with TensorFlow [Video].mp4 29.6 MB
- Code/Section 6/data/cifar-10-batches-bin/data_batch_1.bin 29.3 MB
- Code/Section 6/data/cifar-10-batches-bin/test_batch.bin 29.3 MB
- 4.3-Univariate Logistic Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 25.1 MB
- 1.2-TensorFlows Main Data Structure – Tensors - Building Machine Learning Systems with TensorFlow [Video].mp4 19.6 MB
- 3.4-Multivariate Linear Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 19.2 MB
- 1.5-How TensorBoard Works - Building Machine Learning Systems with TensorFlow [Video].mp4 19.1 MB
- 3.3-Univariate Linear Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 18.8 MB
- 2.4-Project 1 – k-Means Clustering on Synthetic Datasets - Building Machine Learning Systems with TensorFlow [Video].mp4 16.0 MB
- 1.6-Reading Information from Disk - Building Machine Learning Systems with TensorFlow [Video].mp4 15.7 MB
- 2.3-k-Nearest Neighbor - Building Machine Learning Systems with TensorFlow [Video].mp4 15.4 MB
- 6.2-Applying Convolution in TensorFlow - Building Machine Learning Systems with TensorFlow [Video].mp4 15.2 MB
- 1.3-Handling the Computing Workflow – TensorFlows Data Flow Graph - Building Machine Learning Systems with TensorFlow [Video].mp4 14.3 MB
- 5.1-Preliminary Concepts - Building Machine Learning Systems with TensorFlow [Video].mp4 14.0 MB
- 6.6-MNIST Digit Classification - Building Machine Learning Systems with TensorFlow [Video].mp4 13.6 MB
- 5.3-Second Project – Modeling Cars Fuel Efficiency with Non-Linear Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 13.5 MB
- 1.1-The course Overview - Building Machine Learning Systems with TensorFlow [Video].mp4 12.5 MB
- 8.5-Painting with Style – VGG Style Transfer - Building Machine Learning Systems with TensorFlow [Video].mp4 11.8 MB
- 5.4-Third Project – Learning to Classify Wines Multiclass Classification - Building Machine Learning Systems with TensorFlow [Video].mp4 11.3 MB
- 7.4-Univariate Time Series Prediction with Energy Consumption Data - Building Machine Learning Systems with TensorFlow [Video].mp4 10.9 MB
- 5.2-First Project – Non-Linear Synthetic Function Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 10.8 MB
- 6.7-Image Classification with the CIFAR10 Dataset - Building Machine Learning Systems with TensorFlow [Video].mp4 10.2 MB
- 9.2-MacOS Installation - Building Machine Learning Systems with TensorFlow [Video].mp4 10.2 MB
- 4.4-Univariate Logistic Regression with keras - Building Machine Learning Systems with TensorFlow [Video].mp4 10.1 MB
- 4.2-The Logistic Function - Building Machine Learning Systems with TensorFlow [Video].mp4 10.1 MB
- 9.1-Windows Installation - Building Machine Learning Systems with TensorFlow [Video].mp4 9.8 MB
- 3.1-Univariate Linear Modelling Function - Building Machine Learning Systems with TensorFlow [Video].mp4 9.4 MB
- 6.3-Subsampling Operation –Pooling - Building Machine Learning Systems with TensorFlow [Video].mp4 9.0 MB
- 8.2-Alexnet - Building Machine Learning Systems with TensorFlow [Video].mp4 9.0 MB
- 2.5-Project 2 – Nearest Neighbor on Synthetic Datasets - Building Machine Learning Systems with TensorFlow [Video].mp4 8.4 MB
- 7.2-AFundamental Component – Gate Operation and Its Steps - Building Machine Learning Systems with TensorFlow [Video].mp4 7.8 MB
- 4.1-Logistic Function Predecessor – The Logit Functions - Building Machine Learning Systems with TensorFlow [Video].mp4 7.3 MB
- 6.1-Origin of Convolutional Neural Networks - Building Machine Learning Systems with TensorFlow [Video].mp4 7.1 MB
- 7.1-Recurrent Neural Networks - Building Machine Learning Systems with TensorFlow [Video].mp4 7.0 MB
- 2.2-Mechanics of k-Means - Building Machine Learning Systems with TensorFlow [Video].mp4 6.6 MB
- 3.2-Optimizer Methods in TensorFlow – The Train Module - Building Machine Learning Systems with TensorFlow [Video].mp4 6.0 MB
- 6.4-Improving Efficiency – Dropout Operation - Building Machine Learning Systems with TensorFlow [Video].mp4 5.8 MB
- 8.1-Deep Neural Network Definition and Architectures Through Time - Building Machine Learning Systems with TensorFlow [Video].mp4 5.1 MB
- 2.1-Learning from Data –Unsupervised Learning - Building Machine Learning Systems with TensorFlow [Video].mp4 4.8 MB
- 7.3-TensorFlow LSTM Useful Classes and Methods - Building Machine Learning Systems with TensorFlow [Video].mp4 4.3 MB
- 8.4-Residual Networks (ResNet) - Building Machine Learning Systems with TensorFlow [Video].mp4 4.0 MB
- Code/Section 1/Section1.ipynb 2.8 MB
- Code/Section 1/.ipynb_checkpoints/Section1-checkpoint.ipynb 2.8 MB
- 6.5-Convolutional Type Layer Building Methods - Building Machine Learning Systems with TensorFlow [Video].mp4 2.7 MB
- Code/Section 7/Code/data/elec_load.csv 2.3 MB
- 8.3-Inception V3 - Building Machine Learning Systems with TensorFlow [Video].mp4 2.2 MB
- Code/Section 2/Section2.ipynb 707.4 KB
- Code/Section 6/data/blue_jay.jpg 605.9 KB
- Code/Section 8/style.jpg 245.4 KB
- Code/Section 8/content.jpg 181.5 KB
- Code/Section 7/Code/CH7_time_series.ipynb 150.1 KB
- Code/Section 6/data/leopard.jpg 142.7 KB
- Code/Section 3/Section3.ipynb 108.5 KB
- Code/Section 5/CH5_Nonlinear.ipynb 102.4 KB
- Code/Section 6/data/test2.gif 102.2 KB
- Code/Section 6/data/test.gif 95.1 KB
- Code/Section 6/CH6_Mnist_final.ipynb 86.2 KB
- Code/Section 4/CH4_Univariate_logistic_regression.ipynb 55.9 KB
- Code/Section 7/Code/model.py 55.7 KB
- Code/Section 7/Code/utils.py 52.9 KB
- Code/Section 7/Code/sample.py 43.4 KB
- Code/Section 5/Ch5_third_example.ipynb 27.5 KB
- Code/Section 5/CH5_linear_regression_nn.ipynb 19.7 KB
- Code/Section 5/data/mpg.csv 17.3 KB
- Code/Section 6/CH6_CIFAR.ipynb 15.6 KB
- Code/Section 4/Univariate_logistic_regression_keras.ipynb 13.6 KB
- Code/Section 5/data/wine.csv 10.6 KB
- Code/Section 8/stylize.py 8.7 KB
- Code/Section 8/neural_style.py 8.5 KB
- Code/Section 6/CH6_Mnist_final.py 4.7 KB
- content.txt 4.0 KB
- Code/Section 4/CH4_Univariate_logistic_regression.py 3.9 KB
- Code/Section 1/iris.csv 3.7 KB
- Code/Section 8/.ipynb_checkpoints/Cifar10-checkpoint.ipynb 2.8 KB
- Code/Section 7/Code/train.py 2.5 KB
- Code/Section 6/CH6_convolution.ipynb 2.5 KB
- Code/Section 6/CH6_image_subsampling.ipynb 2.3 KB
- Code/Section 3/utils.py 2.3 KB
- Code/Section 8/vgg.py 2.1 KB
- Code/Section 5/CH5_linear_regression_nn.py 2.0 KB
- Code/Section 5/Ch5_third_example.py 1.9 KB
- Code/Section 5/CH5_Nonlinear.py 1.7 KB
- Code/Section 6/CH6_convolution.py 1.4 KB
- Code/Section 6/CH6_image_subsampling.py 1.2 KB
- Code/Section 4/Univariate_logistic_regression_keras.py 1.0 KB
- Code/Section 1/csv_1.0.py 741 bytes
- Code/Section 4/data/CHD.csv 609 bytes
- Code/Section 6/data/cifar-10-batches-bin/readme.html 88 bytes
- Code/Section 8/.ipynb_checkpoints/VGG retraining-checkpoint.ipynb 72 bytes
- Code/Section 6/data/cifar-10-batches-bin/batches.meta.txt 61 bytes
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