index.qmd

---
title: Guides
anchor-sections: false
search: false
listing:
  - id: tensorflow-links
    type: grid
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    fields: [title, description]
    sort: '' # don't sort
    contents: 
      - tensorflow/basics.qmd
      - tensorflow/tensor.qmd
      - tensorflow/autodiff.qmd
      - tensorflow/intro_to_graphs.qmd
      - tensorflow/tensor_slicing.qmd
      # - variable.qmd
      - autograph.qmd
  - id: keras-links
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    contents:
      - keras/sequential_model.qmd
      - keras/functional_api.qmd
      - keras/training_with_built_in_methods.qmd
      - keras/making_new_layers_and_models_via_subclassing.qmd
      - keras/serialization_and_saving.qmd
      - keras/preprocessing_layers.qmd
      - keras/customizing_what_happens_in_fit.qmd
      - keras/writing_a_training_loop_from_scratch.qmd
      - keras/working_with_rnns.qmd
      - keras/understanding_masking_and_padding.qmd
      - keras/writing_your_own_callbacks.qmd
      - keras/transfer_learning.qmd
---

TensorFlow 2 is an end-to-end, open-source machine learning platform.
You can think of it as an infrastructure layer for [differentiable
programming](https://en.wikipedia.org/wiki/Differentiable_programming).
It combines four key abilities:

-   Efficiently executing low-level tensor operations on CPU, GPU, or
    TPU.
-   Computing the gradient of arbitrary differentiable expressions.
-   Scaling computation to many devices, such as clusters of hundreds of
    GPUs.
-   Exporting programs ("graphs") to external runtimes such as servers,
    browsers, mobile and embedded devices.

TensorFlow 2 focuses on simplicity and ease of use, with features like
eager execution, intuitive higher-level APIs, and flexible model
building on any platform.

## TensorFlow

::: {#tensorflow-links}
:::

## Keras

Keras is the high-level API of TensorFlow 2: an approachable,
highly-productive interface for solving machine learning problems, with
a focus on modern deep learning. It provides essential abstractions and
building blocks for developing and shipping machine learning solutions
with high iteration velocity.

Keras empowers engineers and researchers to take full advantage of the
scalability and cross-platform capabilities of TensorFlow 2.

::: {#keras-links}
:::