#jupyter_notebook#jax
Flax is a library for creating neural networks with JAX. It offers a flexible way to build and analyze these networks. The new Flax NNX API makes it easier to work with neural networks by using regular Python objects, which helps in creating, debugging, and analyzing models more efficiently. This means users can express their models in a more intuitive way, making it simpler to develop and modify neural networks. Flax also provides many tools and examples to help users get started quickly.
https://github.com/google/flax
https://mborgerson.com/creating-an-executable-from-a-python-script/
Creating an Executable from a Python Script
Python is one of my favorite programming languages. That being said, if you've ever had to deploy an application written in Python then you know just how painful it can be.
#PyInstaller
http://www.pyinstaller.org/
#PyInstaller is a program that #freezes (#packages) Python programs into #stand_alone#executables, under Windows, Linux, Mac OS X, FreeBSD, Solaris and AIX. Its main advantages over similar tools are that PyInstaller works with Python 2.7 and 3.3—3.5, it builds smaller executables thanks to transparent compression, it is fully multi-platform, and use the OS support to load the dynamic libraries, thus ensuring full compatibility.
https://www.infoworld.com/article/3230202/python/6-essential-libraries-for-every-python-developer.html
6 essential libraries for every Python developer
Whether you're compiling Python for speed, building native UIs for Python desktop apps, or refining existing Python code, these Python projects have you covered
Python has seen wide adoption across industries and disciplines by dint of being easy to work with. But it has also been aided by a wealth of third-party projects—libraries, add-ons, and complementary development efforts—that extend the language to an ever widening range of use cases.
#PyPy
#CFFI(C Foreign Function Interface library)
#PyInstaller
#PBR(Python Build Reasonableness)
#WxPython
#Mypy