Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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Updated
Jul 13, 2024 - Python
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
A Python implementation of global optimization with gaussian processes.
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)
Sequential model-based optimization with a `scipy.optimize` interface
🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO
An object-oriented algebraic modeling language in Python for structured optimization problems.
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
Optax is a gradient processing and optimization library for JAX.
MLBox is a powerful Automated Machine Learning python library.
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
A research toolkit for particle swarm optimization in Python
A library for differentiable robotics.
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.
Portfolio optimization and back-testing.
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