This guide gets you started programming in TensorFlow. Before using this guide, install TensorFlow. To get the most out of this guide, you should know the following:
- How to program in Python.
- At least a little bit about arrays.
- Ideally, something about machine learning. However, if you know little or nothing about machine learning, then this is still the first guide you should read.
TensorFlow provides multiple APIs. The lowest level API–TensorFlow Core– provides you with complete programming control. We recommend TensorFlow Core for machine learning researchers and others who require fine levels of control over their models. The higher level APIs are built on top of TensorFlow Core. These higher level APIs are typically easier to learn and use than TensorFlow Core. In addition, the higher level APIs make repetitive tasks easier and more consistent between different users. A high-level API like tf.contrib.learn helps you manage data sets, estimators, training and inference. Note that a few of the high-level TensorFlow APIs–those whose method names contain
contrib– are still in development. It is possible that some
contrib methods will change or become obsolete in subsequent TensorFlow releases.
This guide begins with a tutorial on TensorFlow Core. Later, we demonstrate how to implement the same model in tf.contrib.learn. Knowing TensorFlow Core principles will give you a great mental model of how things are working internally when you use the more compact higher level API.