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Jonas Zeunert
2025-07-18 22:22:32 +02:00
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@@ -413,12 +413,14 @@ High-Level Keras Complement for implement common architectures stacks,
served as easy to use plug-n-play modules</li>
<li><a
href="https://www.tensorflow.org/probability">Tensorflow-Probability</a>
- Probabalistic programming built on TensorFlow that makes it easy to
- Probabilistic programming built on TensorFlow that makes it easy to
combine probabilistic models and deep learning on modern hardware.</li>
<li><a
href="https://github.com/tensorlayer/TensorLayerX">TensorLayerX</a> -
TensorLayerX: A Unified Deep Learning Framework for All Hardwares,
Backends and OS, including TensorFlow.</li>
<li><a href="https://github.com/rdabra/txeo">Txeo</a> - A modern C++
wrapper for TensorFlow.</li>
</ul>
<p><a name="tools-utils" /></p>
<h2 id="toolsutilities">Tools/Utilities</h2>
@@ -647,7 +649,7 @@ exercise that will teach you how to use TensorFlow and show you how
layers of data can be explored by working with Tensors.</li>
<li><a href="http://www.broadview.com.cn/book/5059">Deep Learning using
TensorLayer</a> - by Hao Dong et al. This book covers both deep learning
and the implmentation by using TensorFlow and TensorLayer.</li>
and the implementation by using TensorFlow and TensorLayer.</li>
<li><a
href="https://www.manning.com/books/tensorflow-in-action">TensorFlow 2.0
in Action</a> - by Thushan Ganegedara. This practical guide to building
@@ -657,7 +659,7 @@ algorithms.</li>
<li><a
href="https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers">Probabilistic
Programming and Bayesian Methods for Hackers</a> - by Cameron
Davidson-Pilon. Introduction to Bayesian methods and probabalistic
Davidson-Pilon. Introduction to Bayesian methods and probabilistic
graphical models using tensorflow-probability (and, alternatively
PyMC2/3).</li>
</ul>
@@ -685,3 +687,5 @@ href="https://github.com/vinta/awesome-python">vinta</a></li>
href="https://code.google.com/p/go-wiki/wiki/Projects#Machine_Learning">this
page</a></li>
</ul>
<p><a href="https://github.com/jtoy/awesome-tensorflow">tensorflow.md
Github</a></p>