文件名称：Python-使用TensorFlowEager构建神经网络的简单教程
文件大小：41.72MB
文件格式：ZIP
更新时间：2022-08-31 01:15:54
Python开发-机器学习
使用TensorFlow Eager构建神经网络的简单教程
【文件预览】：
tensorflow-eager-tutorials-master
----09_recurrent_neural_networks_for_time_series_regression.ipynb(760KB)
----.gitignore(2KB)
----07_convolutional_neural_networks_for_emotion_recognition.ipynb(168KB)
----08_dynamic_recurrent_neural_networks_for_sequence_classification.ipynb(95KB)
----datasets()
--------dummy_text()
--------get_imdb_dataset.sh(197B)
--------aclImdb()
--------load_forecasting()
--------dummy_images()
----data_utils.py(6KB)
----tutorials_graphics()
--------text2tfrecords.png(42KB)
--------02_flowchart.png(97KB)
--------moving_windows_samples.png(96KB)
--------rnn_imdb.png(37KB)
--------04_flowchart.png(80KB)
--------rnn_regression.png(60KB)
--------readbatches.png(24KB)
--------save_restore_model.png(29KB)
--------images2tfrecords.png(30KB)
--------05_flowchart.png(78KB)
--------03_flowchart.png(130KB)
--------01_flowchart.png(58KB)
----06_read_data_in_batches_from_tfrecords.ipynb(87KB)
----01_simple_feedforward_neural_network.ipynb(68KB)
----README.md(4KB)
----models_checkpoints()
--------DemandRNN()
--------SimpleNN()
--------EmotionCNN()
--------ImdbRNN()
----03_save_and_restore_model.ipynb(10KB)
----02_using_metrics_in_eager_mode.ipynb(175KB)
----04_text_data_to_tfrecords.ipynb(8KB)
----05_images_to_tfrecords.ipynb(6KB)