Getting Started¶

For a brief overview of TensorFlow programming fundamentals, see the following guide:

@{$get_started/get_started$Getting Started with TensorFlow}

MNIST has become the canonical dataset for trying out a new machine learning toolkit. We offer three guides that each demonstrate a different approach to training an MNIST model on TensorFlow:

@{$mnist/beginners$MNIST for ML Beginners}, which introduces MNIST through the high-level API.
@{$mnist/pros$Deep MNIST for Experts}, which is more-in depth than “MNIST for ML Beginners,” and assumes some familiarity with machine learning concepts.
@{$mnist/mechanics$TensorFlow Mechanics 101}, which introduces MNIST through the low-level API.

For developers new to TensorFlow, the high-level API is a good place to start. To learn about the high-level API, read the following guides:

@{$get_started/estimator$tf.estimator Quickstart}, which introduces this API.
@{$get_started/input_fn$Building Input Functions}, which takes you into a somewhat more sophisticated use of this API.

TensorBoard is a utility to visualize different aspects of machine learning. The following guides explain how to use TensorBoard:

@{$get_started/summaries_and_tensorboard$TensorBoard: Visualizing Learning}, which gets you started.
@{$get_started/graph_viz$TensorBoard: Graph Visualization}, which explains how to visualize the computational graph. Graph visualization is typically more useful for programmers using the low-level API.