idem

2022-08-27 11:54:55 +02:00
parent 46ea60162b
commit 1694397c86
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@@ -130,6 +130,9 @@ Here we list several useful Python libraries we strongly recommend (if you use a
 * _Scipy_:https://www.scipy.org/ (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering. 
 * _Matplotlib_:https://matplotlib.org/ is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.
 * _Autograd_:https://github.com/HIPS/autograd can automatically differentiate native Python and Numpy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives
+* _JAX_ https://jax.readthedocs.io/en/latest/index.html has now more or less replaced _Autograd_.
+  JAX is Autograd and XLA, brought together for high-performance numerical computing and machine learning research.
+  It provides composable transformations of Python+NumPy programs: differentiate, vectorize, parallelize, Just-In-Time compile to GPU/TPU, and more.
 * _SymPy_:https://www.sympy.org/en/index.html is a Python library for symbolic mathematics. 
 * _scikit-learn_:https://scikit-learn.org/stable/ has simple and efficient tools for machine learning, data mining and data analysis
 * _TensorFlow_:https://www.tensorflow.org/ is a Python library for fast numerical computing created and released by Google
@@ -564,6 +564,9 @@ no setup and runs entirely in the cloud. Try it out!</p>
 <li><p><em>Scipy</em>:<a class="reference external" href="https://www.scipy.org/">https://www.scipy.org/</a> (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.</p></li>
 <li><p><em>Matplotlib</em>:<a class="reference external" href="https://matplotlib.org/">https://matplotlib.org/</a> is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.</p></li>
 <li><p><em>Autograd</em>:<a class="reference external" href="https://github.com/HIPS/autograd">https://github.com/HIPS/autograd</a> can automatically differentiate native Python and Numpy code. It can handle a large subset of Python’s features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives</p></li>
+<li><p><em>JAX</em> <a class="reference external" href="https://jax.readthedocs.io/en/latest/index.html">https://jax.readthedocs.io/en/latest/index.html</a> has now more or less replaced <em>Autograd</em>.
+JAX is Autograd and XLA, brought together for high-performance numerical computing and machine learning research.
+It provides composable transformations of Python+NumPy programs: differentiate, vectorize, parallelize, Just-In-Time compile to GPU/TPU, and more.</p></li>
 <li><p><em>SymPy</em>:<a class="reference external" href="https://www.sympy.org/en/index.html">https://www.sympy.org/en/index.html</a> is a Python library for symbolic mathematics.</p></li>
 <li><p><em>scikit-learn</em>:<a class="reference external" href="https://scikit-learn.org/stable/">https://scikit-learn.org/stable/</a> has simple and efficient tools for machine learning, data mining and data analysis</p></li>
 <li><p><em>TensorFlow</em>:<a class="reference external" href="https://www.tensorflow.org/">https://www.tensorflow.org/</a> is a Python library for fast numerical computing created and released by Google</p></li>