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+# TensorFlow Model Analysis
+
+**TensorFlow Model Analysis (TFMA)** is a library for evaluating TensorFlow
+models. It allows users to evaluate their models on large amounts of data in a
+distributed fashion, using the same metrics defined in their trainer. These
+metrics can also be computed over different slices of data, and the results can
+be visualised in Jupyter Notebooks.
+
+**TFMA may introduce backwards incompatible changes before version 1.0**.
+
+## Installation and Dependencies
+
+The easiest and recommended way to install TFMA is with the PyPI package.
+
+`pip install tensorflow-model-analysis`
+
+Currently TFMA requires that TensorFlow be installed but does not have an
+explicit dependency on TensorFlow as a package. See [TensorFlow
+documentation](https://www.tensorflow.org/install/) for more information on
+installing TensorFlow.
+
+To enable TFMA visualization in Jupyter Notebook, run<sup>1</sup>:
+
+```
+jupyter nbextension enable --py widgetsnbextension
+jupyter nbextension install --py --symlink tensorflow_model_analysis
+jupyter nbextension enable --py tensorflow_model_analysis
+```
+
+TFMA requires [Apache Beam](https://beam.apache.org/) to run distributed
+pipelines. Apache Beam runs in local mode by default, and can also run in
+distributed mode using
+[Google Cloud Dataflow](https://cloud.google.com/dataflow/). TFMA is designed to
+be extensible to other Apache Beam runners.
+
+### Compatible Versions
+
+This is a table of versions known to be compatible with each other, based on
+our testing framework. Other combinations may also work, but are untested.
+
+|tensorflow-model-analysis  |tensorflow    |apache-beam[gcp]|
+|---------------------------|--------------|----------------|
+|GitHub master              |1.6           |2.4.0           |
+
+## Getting Started
+
+For instructions on using TFMA, see the [getting started
+guide](docs/getting_started.md).
+
+<sup>1</sup> If Jupyter is installed in your home directory, add `--user` for
+    all commands; if Jupyter is installed in root or virtualenv is used,
+    `--sys-prefix` might be needed.