TensorFlow 1.x Deep Learning Cookbook 原版电子书+配套代码

【文件属性】：
文件名称：TensorFlow 1.x Deep Learning Cookbook 原版电子书+配套代码
文件大小：36.65MB
文件格式：ZIP
更新时间：2022-02-03 10:39:51
TensorFlow 深度学习 电子书 代码 TensorFlow 1.x Deep Learning Cookbook 原版电子书+配套代码！

【文件预览】：
TensorFlow 1.x Deep Learning Cookbook.pdf
TensorFlow 1.x Deep Learning Cookbook_Code
----Chapter07()
--------Self_Organized_Maps.ipynb(32KB)
--------K-Means Clustering Iris Dataset.ipynb(64KB)
--------Tensorflow_PCA_embeddings.py(1KB)
--------Restricted_boltzmann_Machines_MNIST.ipynb(57KB)
--------Readme.md(330B)
--------colors.csv(286B)
--------PCA_tensorflow.ipynb(110KB)
--------rbm.py(3KB)
--------Restricted_boltzmann_Machines_Recommender_System.ipynb(38KB)
----README.txt(71B)
----Chapter03()
--------Boston_House_Price_Prediction_MLP_with_Keras_Hyperparameter_Tuning.ipynb(229KB)
--------MNIST_with_BPN_hard_way.py(3KB)
--------Boston_House_Price_Prediction_MLP.ipynb(184KB)
--------MNIST_ReLU_cross_entropy.py(2KB)
--------Readme.md(827B)
--------Activation_functions.ipynb(84KB)
--------Boston_House_Price_Prediction_MLP_with_Keras.ipynb(214KB)
--------Single_Layer_Perceptron.ipynb(4KB)
----Chapter08()
--------Sparse_Autoencoder.ipynb(893KB)
--------Stacked_DenoisingAutoencoder_Pretraining.ipynb(78KB)
--------Convolutional_Autoencoder.ipynb(70KB)
--------Readme.md(133B)
--------Denoising_Autoencoder.ipynb(1.56MB)
--------Autoencoder_image_reconstruction.ipynb(890KB)
----Chapter06()
--------checkpoint(213B)
--------shakespeare.py(2KB)
--------shakespeare_input.txt(4.36MB)
--------char_idx.pickle(926B)
--------shakespeare.ipynb(13KB)
--------seq2seq-signal-prediction()
----Chapter01()
--------Selecting_devices.py(1KB)
--------add_two.py(229B)
--------Tensorflow_ An Introduction(39B)
--------tf_upgrade.py(27KB)
--------matrix_manuipulations.py(938B)
--------add_two_vectors.py(515B)
--------matrix_manipulations_2.py(754B)
--------validate_tensorflow.py(373B)
----Chapter05()
--------images()
--------SENTIMENT_ANALYSIS_TFLEARN.ipynb(4KB)
--------IMDB_1DCNN.ipynb(7KB)
--------Visual Q&A.ipynb(17KB)
--------VGG16_KERAS_VIS_INSPECTION.ipynb(213KB)
--------VISUALIZE_TENSORBOARD.ipynb(5KB)
--------.DS_Store(6KB)
--------FULL_labelencoder_trainval.pkl_01.npy(70KB)
--------nsynth()
--------Classifying images with VGGNet, ResNet, Inception, and Xception.ipynb(1.42MB)
--------FULL_labelencoder_trainval.pkl(231B)
--------README.md(887B)
--------MNIST_data()
----Chapter09()
--------dqn_atari.py(9KB)
--------readme.md(211B)
--------policy_gradients_pong.py(6KB)
--------Q_learning_cartpole.py(4KB)
--------nn_random_agent.py(3KB)
--------OpenAI_gym.py(769B)
----Chapter04()
--------CIFAR_CNN_TLEARN.ipynb(4KB)
--------VGG16_TFLEARN.ipynb(4KB)
--------CNN_MINST.ipynb(107KB)
--------ARTISTIC_STYLE.ipynb(736KB)
--------.ipynb_checkpoints()
--------README.md(17B)
--------DEEP_DREAM.ipynb(494KB)
----Software and hardware list.pdf(285KB)
----Chapter02()
--------Simple_linear_regression.py(2KB)
--------Multiple_linear_regression.py(2KB)
--------Reading_csv_preprocessing.py(2KB)
--------Regression(40B)
--------MultiLinearRegressor.ipynb(30KB)
--------MNIST Softmax.ipynb(18KB)
--------boston_housing.csv(62KB)