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# Programmer's Guide
The documents in this unit dive into the details of how TensorFlow
works. The units are as follows:
## High Level APIs
* @{$programmers_guide/eager}, which is the easiest way to use tensorflow.
* @{$programmers_guide/estimators}, which introduces a high-level
TensorFlow API that greatly simplifies ML programming.
* @{$programmers_guide/datasets}, which explains how to
set up data pipelines to read data sets into your TensorFlow program.
## Low Level APIs
* @{$programmers_guide/low_level_intro}, which introduces the
basics of how you can use TensorFlow outside of the high Level APIs.
* @{$programmers_guide/tensors}, which explains how to create,
manipulate, and access Tensors--the fundamental object in TensorFlow.
* @{$programmers_guide/variables}, which details how
to represent shared, persistent state in your program.
* @{$programmers_guide/graphs}, which explains:
* dataflow graphs, which are TensorFlow's representation of computations
as dependencies between operations.
* sessions, which are TensorFlow's mechanism for running dataflow graphs
across one or more local or remote devices.
If you are programming with the low-level TensorFlow API, this unit
is essential. If you are programming with a high-level TensorFlow API
such as Estimators or Keras, the high-level API creates and manages
graphs and sessions for you, but understanding graphs and sessions
can still be helpful.
* @{$programmers_guide/saved_model}, which
explains how to save and restore variables and models.
## Accelerators
* @{$using_gpu} explains how TensorFlow assigns operations to
devices and how you can change the arrangement manually.
* @{$using_tpu} explains how to modify `Estimator` programs to run on a TPU.
## ML Concepts
* @{$programmers_guide/embedding}, which introduces the concept
of embeddings, provides a simple example of training an embedding in
TensorFlow, and explains how to view embeddings with the TensorBoard
Embedding Projector.
## Debugging
* @{$programmers_guide/debugger}, which
explains how to use the TensorFlow debugger (tfdbg).
## TensorBoard
TensorBoard is a utility to visualize different aspects of machine learning.
The following guides explain how to use TensorBoard:
* @{$programmers_guide/summaries_and_tensorboard},
which introduces TensorBoard.
* @{$programmers_guide/graph_viz}, which
explains how to visualize the computational graph.
* @{$programmers_guide/tensorboard_histograms} which demonstrates the how to
use TensorBoard's histogram dashboard.
## Misc
* @{$programmers_guide/version_compat},
which explains backward compatibility guarantees and non-guarantees.
* @{$programmers_guide/faq}, which contains frequently asked
questions about TensorFlow.
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