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diff --git a/g3doc/_toc.yaml b/g3doc/_toc.yaml
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+toc:
+- title: Get Started
+  path: /tfx/model_analysis/get_started
+
+- heading: Examples
+- title: Chicago Taxi (end-to-end)
+  path: https://github.com/tensorflow/model-analysis/tree/master/examples/chicago_taxi
+  status: external
diff --git a/g3doc/api_docs/python/_toc.yaml b/g3doc/api_docs/python/_toc.yaml
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+# Automatically generated file; please do not edit
+toc:
+  - title: tfma
+    section:
+    - title: Overview
+      path: /tfx/model_analysis/api_docs/python/tfma
+    - title: EvaluateAndWriteResults
+      path: /tfx/model_analysis/api_docs/python/tfma/EvaluateAndWriteResults
+    - title: load_eval_result
+      path: /tfx/model_analysis/api_docs/python/tfma/load_eval_result
+    - title: load_eval_results
+      path: /tfx/model_analysis/api_docs/python/tfma/load_eval_results
+    - title: make_eval_results
+      path: /tfx/model_analysis/api_docs/python/tfma/make_eval_results
+    - title: multiple_data_analysis
+      path: /tfx/model_analysis/api_docs/python/tfma/multiple_data_analysis
+    - title: multiple_model_analysis
+      path: /tfx/model_analysis/api_docs/python/tfma/multiple_model_analysis
+    - title: run_model_analysis
+      path: /tfx/model_analysis/api_docs/python/tfma/run_model_analysis
+    - title: SingleSliceSpec
+      path: /tfx/model_analysis/api_docs/python/tfma/SingleSliceSpec
+  - title: tfma.constants
+    section:
+    - title: Overview
+      path: /tfx/model_analysis/api_docs/python/tfma/constants
+  - title: tfma.export
+    section:
+    - title: Overview
+      path: /tfx/model_analysis/api_docs/python/tfma/export
+    - title: build_parsing_eval_input_receiver_fn
+      path: /tfx/model_analysis/api_docs/python/tfma/export/build_parsing_eval_input_receiver_fn
+    - title: make_export_strategy
+      path: /tfx/model_analysis/api_docs/python/tfma/export/make_export_strategy
+  - title: tfma.exporter
+    section:
+    - title: Overview
+      path: /tfx/model_analysis/api_docs/python/tfma/exporter
+    - title: FinalExporter
+      path: /tfx/model_analysis/api_docs/python/tfma/exporter/FinalExporter
+    - title: LatestExporter
+      path: /tfx/model_analysis/api_docs/python/tfma/exporter/LatestExporter
+  - title: tfma.post_export_metrics
+    section:
+    - title: Overview
+      path: /tfx/model_analysis/api_docs/python/tfma/post_export_metrics
+    - title: auc
+      path: /tfx/model_analysis/api_docs/python/tfma/post_export_metrics/auc
+    - title: auc_plots
+      path: /tfx/model_analysis/api_docs/python/tfma/post_export_metrics/auc_plots
+    - title: calibration_plot_and_prediction_histogram
+      path: /tfx/model_analysis/api_docs/python/tfma/post_export_metrics/calibration_plot_and_prediction_histogram
+    - title: confusion_matrix_at_thresholds
+      path: /tfx/model_analysis/api_docs/python/tfma/post_export_metrics/confusion_matrix_at_thresholds
+    - title: example_count
+      path: /tfx/model_analysis/api_docs/python/tfma/post_export_metrics/example_count
+    - title: example_weight
+      path: /tfx/model_analysis/api_docs/python/tfma/post_export_metrics/example_weight
+    - title: precision_recall_at_k
+      path: /tfx/model_analysis/api_docs/python/tfma/post_export_metrics/precision_recall_at_k
+  - title: tfma.version
+    section:
+    - title: Overview
+      path: /tfx/model_analysis/api_docs/python/tfma/version
+  - title: tfma.view
+    section:
+    - title: Overview
+      path: /tfx/model_analysis/api_docs/python/tfma/view
+    - title: render_plot
+      path: /tfx/model_analysis/api_docs/python/tfma/view/render_plot
+    - title: render_slicing_metrics
+      path: /tfx/model_analysis/api_docs/python/tfma/view/render_slicing_metrics
+    - title: render_time_series
+      path: /tfx/model_analysis/api_docs/python/tfma/view/render_time_series
diff --git a/g3doc/api_docs/python/index.md b/g3doc/api_docs/python/index.md
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+# All symbols in TensorFlow Model Analysis
+
+*  <a href="./tfma.md"><code>tfma</code></a>
+*  <a href="./tfma/EvaluateAndWriteResults.md"><code>tfma.EvaluateAndWriteResults</code></a>
+*  <a href="./tfma/SingleSliceSpec.md"><code>tfma.SingleSliceSpec</code></a>
+*  <a href="./tfma/constants.md"><code>tfma.constants</code></a>
+*  <a href="./tfma/export.md"><code>tfma.export</code></a>
+*  <a href="./tfma/export/build_parsing_eval_input_receiver_fn.md"><code>tfma.export.build_parsing_eval_input_receiver_fn</code></a>
+*  <a href="./tfma/export/make_export_strategy.md"><code>tfma.export.make_export_strategy</code></a>
+*  <a href="./tfma/exporter.md"><code>tfma.exporter</code></a>
+*  <a href="./tfma/exporter/FinalExporter.md"><code>tfma.exporter.FinalExporter</code></a>
+*  <a href="./tfma/exporter/LatestExporter.md"><code>tfma.exporter.LatestExporter</code></a>
+*  <a href="./tfma/load_eval_result.md"><code>tfma.load_eval_result</code></a>
+*  <a href="./tfma/load_eval_results.md"><code>tfma.load_eval_results</code></a>
+*  <a href="./tfma/make_eval_results.md"><code>tfma.make_eval_results</code></a>
+*  <a href="./tfma/multiple_data_analysis.md"><code>tfma.multiple_data_analysis</code></a>
+*  <a href="./tfma/multiple_model_analysis.md"><code>tfma.multiple_model_analysis</code></a>
+*  <a href="./tfma/post_export_metrics.md"><code>tfma.post_export_metrics</code></a>
+*  <a href="./tfma/post_export_metrics/auc.md"><code>tfma.post_export_metrics.auc</code></a>
+*  <a href="./tfma/post_export_metrics/auc_plots.md"><code>tfma.post_export_metrics.auc_plots</code></a>
+*  <a href="./tfma/post_export_metrics/calibration_plot_and_prediction_histogram.md"><code>tfma.post_export_metrics.calibration_plot_and_prediction_histogram</code></a>
+*  <a href="./tfma/post_export_metrics/confusion_matrix_at_thresholds.md"><code>tfma.post_export_metrics.confusion_matrix_at_thresholds</code></a>
+*  <a href="./tfma/post_export_metrics/example_count.md"><code>tfma.post_export_metrics.example_count</code></a>
+*  <a href="./tfma/post_export_metrics/example_weight.md"><code>tfma.post_export_metrics.example_weight</code></a>
+*  <a href="./tfma/post_export_metrics/precision_recall_at_k.md"><code>tfma.post_export_metrics.precision_recall_at_k</code></a>
+*  <a href="./tfma/run_model_analysis.md"><code>tfma.run_model_analysis</code></a>
+*  <a href="./tfma/version.md"><code>tfma.version</code></a>
+*  <a href="./tfma/view.md"><code>tfma.view</code></a>
+*  <a href="./tfma/view/render_plot.md"><code>tfma.view.render_plot</code></a>
+*  <a href="./tfma/view/render_slicing_metrics.md"><code>tfma.view.render_slicing_metrics</code></a>
+*  <a href="./tfma/view/render_time_series.md"><code>tfma.view.render_time_series</code></a>
diff --git a/g3doc/api_docs/python/tfma.md b/g3doc/api_docs/python/tfma.md
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+<div itemscope itemtype="http://developers.google.com/ReferenceObject">
+<meta itemprop="name" content="tfma" />
+<meta itemprop="path" content="Stable" />
+<meta itemprop="property" content="DATA_CENTRIC_MODE"/>
+<meta itemprop="property" content="MODEL_CENTRIC_MODE"/>
+<meta itemprop="property" content="VERSION_STRING"/>
+</div>
+
+# Module: tfma
+
+Init module for TensorFlow Model Analysis on notebook.
+
+## Modules
+
+[`constants`](./tfma/constants.md) module: Constants used in TensorFlow Model Analysis.
+
+[`export`](./tfma/export.md) module: Library for exporting the EvalSavedModel.
+
+[`exporter`](./tfma/exporter.md) module: `Exporter` class represents different flavors of model export.
+
+[`post_export_metrics`](./tfma/post_export_metrics.md) module: Library containing helpers for adding post export metrics for evaluation.
+
+[`version`](./tfma/version.md) module: Contains the version string for this release of TFMA.
+
+[`view`](./tfma/view.md) module: View API for Tensorflow Model Analysis.
+
+## Classes
+
+[`class SingleSliceSpec`](./tfma/SingleSliceSpec.md): Specification for a single slice.
+
+## Functions
+
+[`EvaluateAndWriteResults(...)`](./tfma/EvaluateAndWriteResults.md)
+
+[`load_eval_result(...)`](./tfma/load_eval_result.md): Creates an EvalResult object for use with the visualization functions.
+
+[`load_eval_results(...)`](./tfma/load_eval_results.md): Run model analysis for a single model on multiple data sets.
+
+[`make_eval_results(...)`](./tfma/make_eval_results.md): Run model analysis for a single model on multiple data sets.
+
+[`multiple_data_analysis(...)`](./tfma/multiple_data_analysis.md): Run model analysis for a single model on multiple data sets.
+
+[`multiple_model_analysis(...)`](./tfma/multiple_model_analysis.md): Run model analysis for multiple models on the same data set.
+
+[`run_model_analysis(...)`](./tfma/run_model_analysis.md): Runs TensorFlow model analysis.
+
+## Other Members
+
+<h3 id="DATA_CENTRIC_MODE"><code>DATA_CENTRIC_MODE</code></h3>
+
+<h3 id="MODEL_CENTRIC_MODE"><code>MODEL_CENTRIC_MODE</code></h3>
+
+<h3 id="VERSION_STRING"><code>VERSION_STRING</code></h3>
+
diff --git a/g3doc/api_docs/python/tfma/EvaluateAndWriteResults.md b/g3doc/api_docs/python/tfma/EvaluateAndWriteResults.md
@@ -0,0 +1,14 @@
+<div itemscope itemtype="http://developers.google.com/ReferenceObject">
+<meta itemprop="name" content="tfma.EvaluateAndWriteResults" />
+<meta itemprop="path" content="Stable" />
+</div>
+
+# tfma.EvaluateAndWriteResults
+
+``` python
+tfma.EvaluateAndWriteResults(
+    *args,
+    **kwargs
+)
+```
+
diff --git a/g3doc/api_docs/python/tfma/SingleSliceSpec.md b/g3doc/api_docs/python/tfma/SingleSliceSpec.md
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+<div itemscope itemtype="http://developers.google.com/ReferenceObject">
+<meta itemprop="name" content="tfma.SingleSliceSpec" />
+<meta itemprop="path" content="Stable" />
+<meta itemprop="property" content="__eq__"/>
+<meta itemprop="property" content="__init__"/>
+<meta itemprop="property" content="__ne__"/>
+<meta itemprop="property" content="generate_slices"/>
+<meta itemprop="property" content="is_overall"/>
+<meta itemprop="property" content="is_slice_applicable"/>
+</div>
+
+# tfma.SingleSliceSpec
+
+## Class `SingleSliceSpec`
+
+
+
+Specification for a single slice.
+
+This is intended to be an immutable class that specifies a single slice.
+Use this in conjunction with get_slices_for_features_dict to generate slices
+for a dictionary of features.
+
+Examples:
+  - columns = ['age'], features = []
+    This means to slice by the 'age' column.
+  - columns = ['age'], features = [('gender', 'female')]
+    This means to slice by the 'age' column if the 'gender' is 'female'.
+  - For more examples, refer to the tests in slicer_test.py.
+
+<h2 id="__init__"><code>__init__</code></h2>
+
+``` python
+__init__(
+    columns=(),
+    features=()
+)
+```
+
+Initialises a SingleSliceSpec.
+
+#### Args:
+
+* <b>`columns`</b>: an iterable of column names to slice on.
+* <b>`features`</b>: a iterable of features to slice on. Each feature is a
+    (key, value) tuple. Note that the value can be either a string or an
+    int, and the type is taken into account when comparing values, so
+    SingleSliceSpec(features=[('age', '5')]) will *not* match a slice
+    with age=[5] (age is a string in the spec, but an int in the slice).
+
+
+#### Raises:
+
+* <b>`ValueError`</b>: There was overlap between the columns specified in columns
+    and those in features.
+* <b>`ValueError`</b>: columns or features was a string: they should probably be a
+    singleton list containing that string.
+
+
+
+## Methods
+
+<h3 id="__eq__"><code>__eq__</code></h3>
+
+``` python
+__eq__(other)
+```
+
+Return self==value.
+
+<h3 id="__ne__"><code>__ne__</code></h3>
+
+``` python
+__ne__(other)
+```
+
+Return self!=value.
+
+<h3 id="generate_slices"><code>generate_slices</code></h3>
+
+``` python
+generate_slices(accessor)
+```
+
+Generates all slices that match this specification from the data.
+
+Should only be called within this file.
+
+Examples:
+  - columns = [], features = []
+    slice accessor has features age=[5], gender=['f'], interest=['knitting']
+    returns [[]]
+  - columns = ['age'], features = [('gender', 'f')]
+    slice accessor has features age=[5], gender=['f'], interest=['knitting']
+    returns [[('age', 5), ('gender, 'f')]]
+  - columns = ['interest'], features = [('gender', 'f')]
+    slice accessor has features age=[5], gender=['f'],
+    interest=['knitting', 'games']
+    returns [[('gender', 'f'), ('interest, 'knitting')],
+             [('gender', 'f'), ('interest, 'games')]]
+
+#### Args:
+
+* <b>`accessor`</b>: slice accessor.
+
+
+#### Yields:
+
+A SliceKeyType for each slice that matches this specification. Nothing
+will be yielded if there no slices matched this specification. The entries
+in the yielded SliceKeyTypes are guaranteed to be sorted by key names (and
+then values, if necessary), ascending.
+
+<h3 id="is_overall"><code>is_overall</code></h3>
+
+``` python
+is_overall()
+```
+
+Returns True if this specification represents the overall slice.
+
+<h3 id="is_slice_applicable"><code>is_slice_applicable</code></h3>
+
+``` python
+is_slice_applicable(slice_key)
+```
+
+Determines if this slice spec is applicable to a slice of data.
+
+#### Args:
+
+* <b>`slice_key`</b>: The slice as a SliceKeyType
+
+
+#### Returns:
+
+True if the slice_spec is applicable to the given slice, False otherwise.
+
+
+
diff --git a/g3doc/api_docs/python/tfma/constants.md b/g3doc/api_docs/python/tfma/constants.md
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+<div itemscope itemtype="http://developers.google.com/ReferenceObject">
+<meta itemprop="name" content="tfma.constants" />
+<meta itemprop="path" content="Stable" />
+<meta itemprop="property" content="DATA_CENTRIC_MODE"/>
+<meta itemprop="property" content="FEATURES_PREDICTIONS_LABELS_KEY"/>
+<meta itemprop="property" content="MODEL_CENTRIC_MODE"/>
+<meta itemprop="property" content="SLICE_KEYS"/>
+<meta itemprop="property" content="SLICE_KEYS_MATERIALIZED"/>
+<meta itemprop="property" content="UNKNOWN_EVAL_MODE"/>
+</div>
+
+# Module: tfma.constants
+
+Constants used in TensorFlow Model Analysis.
+
+## Other Members
+
+<h3 id="DATA_CENTRIC_MODE"><code>DATA_CENTRIC_MODE</code></h3>
+
+<h3 id="FEATURES_PREDICTIONS_LABELS_KEY"><code>FEATURES_PREDICTIONS_LABELS_KEY</code></h3>
+
+<h3 id="MODEL_CENTRIC_MODE"><code>MODEL_CENTRIC_MODE</code></h3>
+
+<h3 id="SLICE_KEYS"><code>SLICE_KEYS</code></h3>
+
+<h3 id="SLICE_KEYS_MATERIALIZED"><code>SLICE_KEYS_MATERIALIZED</code></h3>
+
+<h3 id="UNKNOWN_EVAL_MODE"><code>UNKNOWN_EVAL_MODE</code></h3>
+
diff --git a/g3doc/api_docs/python/tfma/export.md b/g3doc/api_docs/python/tfma/export.md
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+<div itemscope itemtype="http://developers.google.com/ReferenceObject">
+<meta itemprop="name" content="tfma.export" />
+<meta itemprop="path" content="Stable" />
+<meta itemprop="property" content="EvalInputReceiverType"/>
+</div>
+
+# Module: tfma.export
+
+Library for exporting the EvalSavedModel.
+
+## Functions
+
+[`build_parsing_eval_input_receiver_fn(...)`](../tfma/export/build_parsing_eval_input_receiver_fn.md): Build a eval_input_receiver_fn expecting fed tf.Examples.
+
+[`make_export_strategy(...)`](../tfma/export/make_export_strategy.md): Create an ExportStrategy for EvalSavedModel.
+
+## Other Members
+
+<h3 id="EvalInputReceiverType"><code>EvalInputReceiverType</code></h3>
+