amwi04

numba

NumPy aware dynamic Python compiler using LLVM

scikit-learn

scikit-learn: machine learning in Python

tvm

Open deep learning compiler stack for cpu, gpu and specialized accelerators

celerybeat_pickle

Using pickle for scheduling in beats.

async_client_server

Learning to implement raft from (https://pdos.csail.mit.edu/6.824/schedule.html)

saiona

learn

Ordinary_Differential_Equations

computer-science

:mortar_board: Path to a free self-taught education in Computer Science!

bhav_copy

singa

a distributed deep learning platform

awesome-fraud-detection-papers

A curated list of data mining papers about fraud detection.

opencl_learn

18337

18.337 - Parallel Computing and Scientific Machine Learning

pyopencl

OpenCL integration for Python, plus shiny features

qiskit-tutorials

A collection of Jupyter notebooks showing how to use the Qiskit SDK

compyle

Execute a subset of Python on HPC platforms

dask

Parallel computing with task scheduling

streamz

Real-time stream processing for python

Deeplearning

bayesian-analysis-recipes

A collection of Bayesian data analysis recipes using PyMC3

mslearn-tailspin-spacegame-web

Code used in Microsoft Learn modules to support Azure DevOps

RDKafka.jl

Wrapper for librdkafka

Kalman-and-Bayesian-Filters-in-Python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

pyopencl-examples

Examples for Learning PyOpenCL

mindsdb

Framework to streamline use of neural networks

faust

Python Stream Processing

DeepExperiments

TensorFlow/Keras experiments on computer vision and natural language processing

first_keras

pre-trained-keras-example

Example on how to use pre trained networks on new classification problems.