Getting Started

Getting Started

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

• 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 for ML Beginners, which introduces MNIST through the high-level API.
• Deep MNIST for Experts, which is more-in depth than "MNIST for ML Beginners," and assumes some familiarity with machine learning concepts.
• 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:

• tf.contrib.learn Quickstart, which introduces this API.
• Building Input Functions with tf.contrib.learn, which takes you into a somewhat more sophisticated use of this API.
• Logging and Monitoring Basics with tf.contrib.learn, which explains how to audit the progress of model training.

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

• TensorBoard: Visualizing Learning, which gets you started.
• TensorBoard: Embedding Visualization, which demonstrates how to view and interact with high-dimensional data, such as embeddings-
• TensorBoard: Graph Visualization, which explains how to visualize the computational graph. Graph visualization is typically more useful for programmers using the low-level API.