Stars
🚀 The fast, Pythonic way to build MCP servers and clients.
The official Python SDK for Model Context Protocol servers and clients
Automagically redraw any image into a painting by means of artificial evolution.
A Python library for the Docker Engine API
contaiNERD CTL - Docker-compatible CLI for containerd, with support for Compose, Rootless, eStargz, OCIcrypt, IPFS, ...
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
Application of genetic algorithm using PyGAD for Travelling Salesman Problem. Finding shortest route to every Starbucks in London and back again.
The tool for managing conda-forge feedstocks.
This repo contains the code for neural network weight optimisation using 4 evolutionary algorithms.
A CLI tool and go library which recommends instance types based on resource criteria like vcpus and memory
Extended pickling support for Python objects
🌐 The easiest way to parse and modify URLs in Python.
The command line interface for Gradient - https://gradient.paperspace.com
The combination of the keras and pyGAD
Python API for ML inferencing and transfer-learning on Coral devices
MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.
Source Code for 'Building Android Apps in Python Using Kivy with Android Studio' by Ahmed Fawzy Mohamed Gad
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Official repository for Spyder - The Scientific Python Development Environment
PyTorch Implementation of the CVPR'19 Paper "Practical Full Resolution Learned Lossless Image Compression"
Pytorch implementation of High-Fidelity Generative Image Compression + Routines for neural image compression
Visit PixelLib's official documentation https://pixellib.readthedocs.io/en/latest/
optimization of speed of a mutate function from the excellent pygad project