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 ...
Get Learning TensorFlow now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.