added info to jax

2022-08-27 11:51:24 +02:00
parent d925c29864
commit c033cc0536
7 changed files with 325 additions and 318 deletions
@@ -361,6 +361,7 @@ MathJax.Hub.Config({
 <li> <a href="https://www.scipy.org/" target="_self">Scipy</a> (pronounced &#8220;Sigh Pie&#8221;) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.</li> 
 <li> <a href="https://matplotlib.org/" target="_self">Matplotlib</a> is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.</li>
 <li> <a href="https://github.com/HIPS/autograd" target="_self">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</li>
+<li> <a href="https://jax.readthedocs.io/en/latest/index.html" target="_self">JAX</a> has now more or less replaced <b>Autograd</b>. 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.</li>
 <li> <a href="https://www.sympy.org/en/index.html" target="_self">SymPy</a> is a Python library for symbolic mathematics.</li> 
 <li> <a href="https://scikit-learn.org/stable/" target="_self">scikit-learn</a> has simple and efficient tools for machine learning, data mining and data analysis</li>
 <li> <a href="https://www.tensorflow.org/" target="_self">TensorFlow</a> is a Python library for fast numerical computing created and released by Google</li>
@@ -856,6 +856,7 @@ no setup and runs entirely in the cloud. Try it out!
 <p><li> <a href="https://www.scipy.org/" target="_blank">Scipy</a> (pronounced &#8220;Sigh Pie&#8221;) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.</li> 
 <p><li> <a href="https://matplotlib.org/" target="_blank">Matplotlib</a> is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.</li>
 <p><li> <a href="https://github.com/HIPS/autograd" target="_blank">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</li>
+<p><li> <a href="https://jax.readthedocs.io/en/latest/index.html" target="_blank">JAX</a> has now more or less replaced <b>Autograd</b>. 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.</li>
 <p><li> <a href="https://www.sympy.org/en/index.html" target="_blank">SymPy</a> is a Python library for symbolic mathematics.</li> 
 <p><li> <a href="https://scikit-learn.org/stable/" target="_blank">scikit-learn</a> has simple and efficient tools for machine learning, data mining and data analysis</li>
 <p><li> <a href="https://www.tensorflow.org/" target="_blank">TensorFlow</a> is a Python library for fast numerical computing created and released by Google</li>
@@ -903,6 +903,7 @@ no setup and runs entirely in the cloud. Try it out!
 <li> <a href="https://www.scipy.org/" target="_blank">Scipy</a> (pronounced &#8220;Sigh Pie&#8221;) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.</li> 
 <li> <a href="https://matplotlib.org/" target="_blank">Matplotlib</a> is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.</li>
 <li> <a href="https://github.com/HIPS/autograd" target="_blank">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</li>
+<li> <a href="https://jax.readthedocs.io/en/latest/index.html" target="_blank">JAX</a> has now more or less replaced <b>Autograd</b>. 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.</li>
 <li> <a href="https://www.sympy.org/en/index.html" target="_blank">SymPy</a> is a Python library for symbolic mathematics.</li> 
 <li> <a href="https://scikit-learn.org/stable/" target="_blank">scikit-learn</a> has simple and efficient tools for machine learning, data mining and data analysis</li>
 <li> <a href="https://www.tensorflow.org/" target="_blank">TensorFlow</a> is a Python library for fast numerical computing created and released by Google</li>
@@ -980,6 +980,7 @@ no setup and runs entirely in the cloud. Try it out!
 <li> <a href="https://www.scipy.org/" target="_blank">Scipy</a> (pronounced &#8220;Sigh Pie&#8221;) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.</li> 
 <li> <a href="https://matplotlib.org/" target="_blank">Matplotlib</a> is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.</li>
 <li> <a href="https://github.com/HIPS/autograd" target="_blank">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</li>
+<li> <a href="https://jax.readthedocs.io/en/latest/index.html" target="_blank">JAX</a> has now more or less replaced <b>Autograd</b>. 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.</li>
 <li> <a href="https://www.sympy.org/en/index.html" target="_blank">SymPy</a> is a Python library for symbolic mathematics.</li> 
 <li> <a href="https://scikit-learn.org/stable/" target="_blank">scikit-learn</a> has simple and efficient tools for machine learning, data mining and data analysis</li>
 <li> <a href="https://www.tensorflow.org/" target="_blank">TensorFlow</a> is a Python library for fast numerical computing created and released by Google</li>
@@ -564,6 +564,7 @@ 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