If you are new to machine learning, we recommend taking the following online course prior to diving into TensorFlow documentation:
- Machine Learning Crash Course, which introduces machine learning concepts and encourages experimentation with existing TensorFlow code.
TensorFlow is a tool for machine learning. While it contains a wide range of functionality, TensorFlow is mainly designed for deep neural network models.
TensorFlow provides many APIs. This section focuses on the high-level APIs. If you are new to TensorFlow, begin by reading one of the following documents:
- Get Started with Eager Execution is for machine learning beginners and uses Eager Execution.
- Get Started with Graph Execution is also for machine learning beginners and uses Graphs and Sessions.
- Get Started with Estimators assumes some machine learning background and uses an Estimator.
Then, read the following documents, which demonstrate the key features in the high-level APIs:
- Checkpoints, which explains how to save training progress and resume where you left off.
- Feature Columns, which shows how an Estimator can handle a variety of input data types without changes to the model.
- Datasets Quick Start, which introduces TensorFlow's input pipelines.
- Creating Custom Estimators, which demonstrates how to build and train models you design yourself.
For more advanced users: