Building Machine Learning Systems with TensorFlow [Video]

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Building Machine Learning Systems with TensorFlow [Video]

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文件大小： 1.09G
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收录时间：2017-07-03
最近下载：2025-06-01

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文件列表

  • 1.1-The course Overview - Building Machine Learning Systems with TensorFlow [Video].mp4 13.2 MB
  • 1.2-TensorFlows Main Data Structure – Tensors - Building Machine Learning Systems with TensorFlow [Video].mp4 20.6 MB
  • 1.3-Handling the Computing Workflow – TensorFlows Data Flow Graph - Building Machine Learning Systems with TensorFlow [Video].mp4 15.0 MB
  • 1.4-Basic Tensor Methods - Building Machine Learning Systems with TensorFlow [Video].mp4 31.0 MB
  • 1.5-How TensorBoard Works - Building Machine Learning Systems with TensorFlow [Video].mp4 20.0 MB
  • 1.6-Reading Information from Disk - Building Machine Learning Systems with TensorFlow [Video].mp4 16.5 MB
  • 2.1-Learning from Data –Unsupervised Learning - Building Machine Learning Systems with TensorFlow [Video].mp4 5.1 MB
  • 2.2-Mechanics of k-Means - Building Machine Learning Systems with TensorFlow [Video].mp4 7.0 MB
  • 2.3-k-Nearest Neighbor - Building Machine Learning Systems with TensorFlow [Video].mp4 16.1 MB
  • 2.4-Project 1 – k-Means Clustering on Synthetic Datasets - Building Machine Learning Systems with TensorFlow [Video].mp4 16.8 MB
  • 2.5-Project 2 – Nearest Neighbor on Synthetic Datasets - Building Machine Learning Systems with TensorFlow [Video].mp4 8.8 MB
  • 3.1-Univariate Linear Modelling Function - Building Machine Learning Systems with TensorFlow [Video].mp4 9.9 MB
  • 3.2-Optimizer Methods in TensorFlow – The Train Module - Building Machine Learning Systems with TensorFlow [Video].mp4 6.3 MB
  • 3.3-Univariate Linear Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 19.7 MB
  • 3.4-Multivariate Linear Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 20.1 MB
  • 4.1-Logistic Function Predecessor – The Logit Functions - Building Machine Learning Systems with TensorFlow [Video].mp4 7.7 MB
  • 4.2-The Logistic Function - Building Machine Learning Systems with TensorFlow [Video].mp4 10.6 MB
  • 4.3-Univariate Logistic Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 26.3 MB
  • 4.4-Univariate Logistic Regression with keras - Building Machine Learning Systems with TensorFlow [Video].mp4 10.6 MB
  • 5.1-Preliminary Concepts - Building Machine Learning Systems with TensorFlow [Video].mp4 14.7 MB
  • 5.2-First Project – Non-Linear Synthetic Function Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 11.3 MB
  • 5.3-Second Project – Modeling Cars Fuel Efficiency with Non-Linear Regression - Building Machine Learning Systems with TensorFlow [Video].mp4 14.2 MB
  • 5.4-Third Project – Learning to Classify Wines Multiclass Classification - Building Machine Learning Systems with TensorFlow [Video].mp4 11.8 MB
  • 6.1-Origin of Convolutional Neural Networks - Building Machine Learning Systems with TensorFlow [Video].mp4 7.4 MB
  • 6.2-Applying Convolution in TensorFlow - Building Machine Learning Systems with TensorFlow [Video].mp4 15.9 MB
  • 6.3-Subsampling Operation –Pooling - Building Machine Learning Systems with TensorFlow [Video].mp4 9.4 MB
  • 6.4-Improving Efficiency – Dropout Operation - Building Machine Learning Systems with TensorFlow [Video].mp4 6.1 MB
  • 6.5-Convolutional Type Layer Building Methods - Building Machine Learning Systems with TensorFlow [Video].mp4 2.8 MB
  • 6.6-MNIST Digit Classification - Building Machine Learning Systems with TensorFlow [Video].mp4 14.3 MB
  • 6.7-Image Classification with the CIFAR10 Dataset - Building Machine Learning Systems with TensorFlow [Video].mp4 10.7 MB
  • 7.1-Recurrent Neural Networks - Building Machine Learning Systems with TensorFlow [Video].mp4 7.3 MB
  • 7.2-AFundamental Component – Gate Operation and Its Steps - Building Machine Learning Systems with TensorFlow [Video].mp4 8.2 MB
  • 7.3-TensorFlow LSTM Useful Classes and Methods - Building Machine Learning Systems with TensorFlow [Video].mp4 4.5 MB
  • 7.4-Univariate Time Series Prediction with Energy Consumption Data - Building Machine Learning Systems with TensorFlow [Video].mp4 11.4 MB
  • 7.5-Writing Music a la Bach - Building Machine Learning Systems with TensorFlow [Video].mp4 31.9 MB
  • 8.1-Deep Neural Network Definition and Architectures Through Time - Building Machine Learning Systems with TensorFlow [Video].mp4 5.4 MB
  • 8.2-Alexnet - Building Machine Learning Systems with TensorFlow [Video].mp4 9.4 MB
  • 8.3-Inception V3 - Building Machine Learning Systems with TensorFlow [Video].mp4 2.3 MB
  • 8.4-Residual Networks (ResNet) - Building Machine Learning Systems with TensorFlow [Video].mp4 4.2 MB
  • 8.5-Painting with Style – VGG Style Transfer - Building Machine Learning Systems with TensorFlow [Video].mp4 12.4 MB
  • 9.1-Windows Installation - Building Machine Learning Systems with TensorFlow [Video].mp4 10.3 MB
  • 9.2-MacOS Installation - Building Machine Learning Systems with TensorFlow [Video].mp4 10.6 MB
  • Code/Section 1/.ipynb_checkpoints/Section1-checkpoint.ipynb 2.9 MB
  • Code/Section 1/csv_1.0.py 741 Bytes
  • Code/Section 1/iris.csv 3.8 kB
  • Code/Section 1/Section1.ipynb 2.9 MB
  • Code/Section 2/Section2.ipynb 724.4 kB
  • Code/Section 3/Section3.ipynb 111.1 kB
  • Code/Section 3/utils.py 2.3 kB
  • Code/Section 4/CH4_Univariate_logistic_regression.ipynb 57.3 kB
  • Code/Section 4/CH4_Univariate_logistic_regression.py 4.0 kB
  • Code/Section 4/data/CHD.csv 609 Bytes
  • Code/Section 4/Univariate_logistic_regression_keras.ipynb 13.9 kB
  • Code/Section 4/Univariate_logistic_regression_keras.py 1.1 kB
  • Code/Section 5/CH5_linear_regression_nn.ipynb 20.2 kB
  • Code/Section 5/CH5_linear_regression_nn.py 2.0 kB
  • Code/Section 5/CH5_Nonlinear.ipynb 104.8 kB
  • Code/Section 5/CH5_Nonlinear.py 1.7 kB
  • Code/Section 5/Ch5_third_example.ipynb 28.1 kB
  • Code/Section 5/Ch5_third_example.py 1.9 kB
  • Code/Section 5/data/mpg.csv 17.7 kB
  • Code/Section 5/data/wine.csv 10.9 kB
  • Code/Section 6/CH6_CIFAR.ipynb 16.0 kB
  • Code/Section 6/CH6_convolution.ipynb 2.5 kB
  • Code/Section 6/CH6_convolution.py 1.4 kB
  • Code/Section 6/CH6_image_subsampling.ipynb 2.3 kB
  • Code/Section 6/CH6_image_subsampling.py 1.3 kB
  • Code/Section 6/CH6_Mnist_final.ipynb 88.3 kB
  • Code/Section 6/CH6_Mnist_final.py 4.8 kB
  • Code/Section 6/data/blue_jay.jpg 620.5 kB
  • Code/Section 6/data/cifar-10-batches-bin/batches.meta.txt 61 Bytes
  • Code/Section 6/data/cifar-10-batches-bin/data_batch_1.bin 30.7 MB
  • Code/Section 6/data/cifar-10-batches-bin/readme.html 88 Bytes
  • Code/Section 6/data/cifar-10-batches-bin/test_batch.bin 30.7 MB
  • Code/Section 6/data/leopard.jpg 146.1 kB
  • Code/Section 6/data/test.gif 97.4 kB
  • Code/Section 6/data/test2.gif 104.6 kB
  • Code/Section 7/Code/CH7_time_series.ipynb 153.7 kB
  • Code/Section 7/Code/data/elec_load.csv 2.4 MB
  • Code/Section 7/Code/model.py 57.0 kB
  • Code/Section 7/Code/sample.py 44.5 kB
  • Code/Section 7/Code/train.py 2.5 kB
  • Code/Section 7/Code/utils.py 54.1 kB
  • Code/Section 8/.ipynb_checkpoints/Cifar10-checkpoint.ipynb 2.8 kB
  • Code/Section 8/.ipynb_checkpoints/VGG retraining-checkpoint.ipynb 72 Bytes
  • Code/Section 8/content.jpg 185.8 kB
  • Code/Section 8/imagenet-vgg-verydeep-19.mat 576.0 MB
  • Code/Section 8/neural_style.py 8.7 kB
  • Code/Section 8/style.jpg 251.3 kB
  • Code/Section 8/stylize.py 8.9 kB
  • Code/Section 8/vgg.py 2.2 kB
  • content.txt 4.0 kB

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