Have a repository full of Jupyter notebooks? With Binder,

open those notebooks in an executable environment,

making your code immediately reproducible by anyone, anywhere.

The nteract project is an ecosystem of open source tools to

enable people to build their own front-ends and workflows

on top of the Jupyter ecosystem.

conda-forge is community led collection of recipes, build infrastructure

and distributions. Conda-forge currently build conda packages for Linux,

Mac, Windows, ARM, and Power8 architectures. Conda-forge has 1400 members

in its GitHub organization and >7000 repositories. The conda-forge channel

has about 80 million downloads a month, and growing.

Conda-forge is an official NumFOCUS project.

SciKit-Learn provides simple and efficient tools for data mining and

data analysis which are accessible to everybody, and reusable in

various contexts. It is built on NumPy, SciPy, and matplotlib.

xtensor provides an extensible expression system enabling lazy broadcasting, an API following the idioms of the C++ standard library, and tools to manipulate array expressions and build upon xtensor. xtensor containers are inspired by NumPy, the Python array programming library. Adaptors for existing data structures to be plugged into our expression system can easily be written.

xtensor requires a modern C++ compiler supporting C++14.

Array interface object for Python with pluggable backends and a multiple-dispatch mechanism for defining down-stream functions.

CORRECTION: In the episode Hameer implied moving data from GPUs to CPUs won’t be a problem in PCIe 4,0. It’s actually in an Intel-proposed extension to PCIe 5.0.

It provides transparent conversion of objects between Javascript and Python. When inside a browser, this means Python has full access to the Web APIs.

While closely related to the iodide project, Pyodide may be used standalone in any context where you want to run Python inside a web browser.

PyMC3 is a probabilistic programming package for Python that allows users

to fit Bayesian models using a variety of numerical methods, most notably

Markov chain Monte Carlo (MCMC) and variational inference (VI).

TensorFlow is an end-to-end open source platform for machine learning.

It has a comprehensive, flexible ecosystem of tools, libraries and

community resources that lets researchers push the state-of-the-art

in ML and developers easily build and deploy ML powered applications.

Chainer is a powerful, flexible and intuitive deep learning framework.

Chainer supports CUDA computation. It only requires a few lines of code to

leverage a GPU. It also runs on multiple GPUs with little effort.

Chainer supports various network architectures including feed-forward nets,

convnets, recurrent nets and recursive nets. It also supports per-batch

architectures. Forward computation can include any control flow statements

of Python without lacking the ability of backpropagation. It makes code

intuitive and easy to debug.