Learning TensorFlow

Index

Symbols

• .assign(), Pretrained Word Embeddings, Assigning Loaded Weights
• .compile(), Sequential model
• .eval(), Tensor Arrays and Shapes
• .evaluate(), Linear Regression
• .fit(), Linear Regression, FeatureColumn, CNN, Sequential model
• .get_variable_value(), FeatureColumn
• .meta checkpoint files, The Saver Class
• .name attribute, Names
• .optimizers, Sequential model
• .run() method, Creating a Session and Running It
• .save(), The Saver Class
• .__enter__(), Constructing and Managing Our Graph
• .__exit__(), Constructing and Managing Our Graph
• <Estimator>.predict(), DNN Classifier
• @property decorator, Class encapsulation

A

• abstraction libraries
  • abstraction illustration, Chapter Overview
  • benefits of, A High-Level Overview, Chapter Overview
  • contrib.learn, contrib.learn-Homemade CNN with contrib.learn
  • popular libraries, High-Level Survey
  • regularization and, Regularization
  • TFLearn, TFLearn-Downloading and using a pretrained model
• acknowledgments, Acknowledgments
• activation functions, Convolution
• aliases, Installing TensorFlow
• argparse module, tf.app.flags
• arguments
  • callbacks, Sequential model
  • feed_dict argument, Softmax Regression, The Input Pipeline
  • fetches argument, Fetches
  • ksize argument, Pooling
  • num-epochs argument, tf.train.string_input_producer() and tf.TFRecordReader()
  • perm argument, Applying the RNN step with tf.scan()
  • shape argument, Placeholders
  • strides argument, Convolution
• arrays, Tensor Arrays and Shapes-Name scopes
• .assign(), Pretrained Word Embeddings, Assigning Loaded Weights
• asynchronous training, What Is the Goal ...