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@achoum @copybara-github
achoum authored and copybara-github committed Apr 16, 2024
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171 changes: 123 additions & 48 deletions documentation/_index.yaml
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Expand Up @@ -26,47 +26,100 @@ landing_page:
- classname: devsite-landing-row-50
description: >
<p>
<img src="image/logo.png" />
<img src="image/logo.png" style="display:block; width: 375px;" />
</p>
<div style="padding: 24px; padding-bottom: 15px; border: 1px solid #afafaf; border-radius: 16px; margin: 25px;" >
<img src="image/ydf_logo.png" style="width: 240px; margin: auto; display: block;" >
<p style="font-weight: bold;">
<a href="https://ydf.readthedocs.io">YDF</a> is Google's new library to train Decision Forests.
</p>
<p>
YDF extends the power of TF-DF, offering new features, a simplified API, faster training times, updated documentation, and enhanced compatibility with popular ML libraries.
</p>
<p>
<a class="button button-primary button-tfo-announcement" href="https://ydf.readthedocs.io" style="display: block; margin: auto; width: 171px; text-align: center; background: linear-gradient(90deg, #ff6f00, #ff9100);">Go to new website</a>
</p>
<ul style="margin: auto; display: block; width: 192px; font-size: smaller;">
<li style="margin: 0px;" ><a href="https://ydf.readthedocs.io/en/latest/tutorial/migrating_to_ydf/">Migration guide</a></li>
<li style="margin: 0px;" ><a href="https://ydf.readthedocs.io/en/latest/faq/#python-ydf-and-tf-df">FAQ</a></li>
</ul>
</div>
<p>
<p>
<b>TensorFlow Decision Forests</b> (<b>TF-DF</b>) is a library to train, run and
interpret <a href="https://ydf.readthedocs.io/en/latest/intro_df.html">decision forest</a>
models (e.g., Random Forests, Gradient Boosted Trees) in TensorFlow.
TF-DF supports classification, regression, ranking and uplifting.
It is available on Linux and Mac. Window users can use WSL+Linux.
<p>
<p>
TF-DF is powered by <a
href="https://github.com/google/yggdrasil-decision-forests">Yggdrasil Decision Forest</a> (<b>YDF</b>), a
library to train and use decision forests in c++, JavaScript, CLI, and Go. TF-DF models are <a href="https://ydf.readthedocs.io/en/latest/convert_model.html#convert-a-a-tensorflow-decision-forests-model-to-a-yggdrasil-model">compatible</a> with YDF models, and vice versa.
</p>
<p>
<i>Keywords: Decision Forests, TensorFlow, Random Forest, Gradient Boosted Trees, CART, model interpretation.</i>
</p>
<h3>Documentation & Resources</h3>
<p>
The following resources are available:
<ul>
<ul style="line-height: 1em;">
<li><a href="https://www.tensorflow.org/decision_forests/tutorials">Guides and tutorials</a></li>
<li><a href="https://www.tensorflow.org/decision_forests/api_docs/python/tfdf/all_symbols">API reference</a></li>
<li><a href="https://ydf.readthedocs.io/">YDF documentation (also applicable to TF-DF)</a></li>
<li><a href="https://developers.google.com/machine-learning/decision-forests">Google Developers class on decision forests</a></li>
<li><a href="https://www.tensorflow.org/decision_forests/simple_ml_for_sheets">Use Simple ML for Sheets to train models in your Google Sheets</a></li>
<li><a href="https://developers.google.com/machine-learning/decision-forests">Google Developers' Decision Forests online class</a></li>
</ul>
</p>
<h3>Community</h3>
<li><a href="https://discuss.tensorflow.org">TensorFlow forum</a></li>
<p>
<ul style="line-height: 1em;">
<li><a href="https://github.com/google/yggdrasil-decision-forests">YDF on Github</a></li>
<li><a href="https://github.com/tensorflow/decision-forests">TensorFlow Decision Forest on Github</a></li>
<li><a href="https://github.com/google/yggdrasil-decision-forests">Yggdrasil Decision Forest on Github</a></li>
<li><a href="https://discuss.tensorflow.org">TensorFlow forum</a></li>
</ul>
</p>
<h3>Contributing</h3>
<p>
Contributions to TensorFlow Decision Forests and Yggdrasil Decision Forests are welcome.
If you want to contribute, make sure to review the <a href="developer_manual">developer
manual</a>.
</p>
code_block: |
<style>
.tabs {
position: relative;
min-height: 200px;
clear: both;
margin: 25px 0;
}
.tab {
float: left;
}
.tab label {
padding: 10px;
position: relative;
border-bottom: 3px none #293241;
font: var(--devsite-link-font, 500 14px / 20px var(--devsite-primary-font-family));
color: #293241;
}
.tab [type=radio] {
display: none;
}
.content {
position: absolute;
top: 28px;
left: 0;
right: 0;
bottom: 0;
padding-top: 25px;
display: none;
}
[type=radio]:checked ~ label {
z-index: 2;
border-bottom: 3px solid #293241;
}
[type=radio]:checked ~ label ~ .content {
z-index: 1;
display: block;
}
devsite-code::after {
display: none !important;
}
</style>
<div class="tabs">
<div class="tab">
<input type="radio" id="tab-1" name="tab-group-1" checked>
<label for="tab-1">TF-DF</label>
<div class="content">
<pre class = "prettyprint">
# Install TF-DF
!pip install tensorflow tensorflow_decision_forests
Expand All @@ -90,37 +143,59 @@ landing_page:
# Summary of the model structure.
model.summary()
# Evaluate the model.
model.evaluate(test_ds)
# Compute model accuracy.
model.compile(metrics=["accuracy"])
model.evaluate(test_ds, return_dict=True)
# Export the model to a SavedModel.
model.save("project/model")
</pre>
</div>
</div>
- classname: devsite-landing-row-cards
items:
# - heading: "Introducing TensorFlow Decision Forests"
# image_path: /resources/images/tf-logo-card-16x9.png
# path: https://blog.tensorflow.org
# buttons:
# - label: "Read on TensorFlow blog"
# path: https://blog.tensorflow.org
# - heading: "TensorFlow Decision Forests video"
# youtube_id: 3d34Hkf7KXA
# buttons:
# - label: Watch the video
# path: https://www.youtube.com/watch?v=3d34Hkf7KXA
- heading: "TensorFlow Decision Forests on GitHub"
# # Add the image back when more cards are added.
# image_path: /resources/images/github-card-16x9.png
path: https://github.com/tensorflow/decision-forests
buttons:
- label: "View on GitHub"
path: https://github.com/tensorflow/decision-forests
- heading: "Yggdrasil Decision Forests on GitHub"
# # Add the image back when more cards are added.
# image_path: /resources/images/github-card-16x9.png
path: https://github.com/google/yggdrasil-decision-forests
buttons:
- label: "View on GitHub"
path: https://github.com/google/yggdrasil-decision-forests
<div class="tab">
<input type="radio" id="tab-2" name="tab-group-1">
<label for="tab-2">YDF <span style="font-size: small; border-radius: 5px; padding: 2px 4px; margin-left: 5px; background: linear-gradient(90deg, #5bb53d, #0d9d11); color: white;">new api</span></label>
<div class="content">
<a href="https://colab.research.google.com/github/google/yggdrasil-decision-forests/blob/main/documentation/public/docs/tutorial/usage_example.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg"></a>
<pre class = "prettyprint">
# Install YDF
!pip install ydf -U
import ydf
import pandas as pd
# Load a dataset with Pandas
ds_path = "https://raw.githubusercontent.com/google/yggdrasil-decision-forests/main/yggdrasil_decision_forests/test_data/dataset/"
train_ds = pd.read_csv(ds_path + "adult_train.csv")
test_ds = pd.read_csv(ds_path + "adult_test.csv")
# Train a Gradient Boosted Trees model
model = ydf.GradientBoostedTreesLearner(label="income").train(train_ds)
# Look at a model (input features, training logs, structure, etc.)
model.describe()
# Evaluate a model (e.g. roc, accuracy, confusion matrix, confidence intervals)
model.evaluate(test_ds)
# Generate predictions
model.predict(test_ds)
# Analyse a model (e.g. partial dependence plot, variable importance)
model.analyze(test_ds)
# Benchmark the inference speed of a model
model.benchmark(test_ds)
# Save the model
model.save("/tmp/my_model")
# Export the model as a TensorFlow Saved Model
model.to_tensorflow_saved_model("/tmp/my_saved_model")
</pre>
</div>
</div>
</div>
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