Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
TFX is an end-to-end platform for deploying production ML pipelines
Machine learning on FPGAs using HLS
Awesome machine learning for combinatorial optimization papers.
SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
Deep and online learning with spiking neural networks in Python
The RF and reverse engineering framework for everyone. Follow and ★ to show your support!
A deep learning package for many-body potential energy representation and molecular dynamics
Python Stream Processing
:cloud: :rocket: :bar_chart: :chart_with_upwards_trend: Evaluating state of the art in AI
🤖 A Python library for learning and evaluating knowledge graph embeddings
Library for training machine learning models with privacy for training data
Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)
Elyra extends JupyterLab with an AI centric approach.
Training PyTorch models with differential privacy
Save your dotfiles once, deploy them everywhere
Implementation of "BitNet: Scaling 1-bit Transformers for Large Language Models" in pytorch
Gaussian processes in TensorFlow
A Python package for time series classification
Large-scale LLM inference engine
Magenta RealTime 2: An Open-Weights Live Music Model
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Reference implementations of MLPerf® training benchmarks
Python AutoML for Trading Systems and Sports Betting
Synthetic data curation for post-training and structured data extraction
A lightweight library for PyTorch training tools and utilities
Automated Machine Learning on Kubernetes
Simulation of spiking neural networks (SNNs) using PyTorch.
MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.
TensorLy: Tensor Learning in Python.
DLRover: An Automatic Distributed Deep Learning System
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Tika-Python is a Python binding to the Apache Tikaâ„¢ REST services allowing Tika to be called natively in the Python community.
Machine learning with dataframes
A PyTorch library and evaluation platform for end-to-end compression research
The backend agents build with - Multimodal database, orchestration, and serving in one file
Extensible, parallel implementations of t-SNE
:red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps
High-quality implementations of standard and SOTA methods on a variety of tasks.
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
Python Streaming DataFrames for Kafka
List of papers studying machine learning through the lens of category theory
TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.
Multi-class confusion matrix library in Python
Fast and customizable framework for automatic ML model creation (AutoML)
Machine learning for NeuroImaging in Python
Production-shaped MLOps Python package and reference implementation of the MLOps Coding Course: MLflow, scikit-learn, Pydantic, Pandera, uv, and mise.
Extra blocks for scikit-learn pipelines.
🦙 Integrating LLMs into structured NLP pipelines
MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.
Unsupervised time series anomaly detection library
Build, train, optimize, and run computer vision models locally, from raw images to live inference. Open source, optimized for Intel XPU (CPU-only and CUDA also supported).
Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
Survival analysis built on top of scikit-learn
Expressive statecharts and FSMs for modern Python.
Pruna is a model optimization framework built for developers, enabling you to deliver faster, more efficient models with minimal overhead.
Transpile trained scikit-learn estimators to C, Java, JavaScript and others.
A comprehensive, step-by-step guide to learning Machine Learning from absolute basics to advanced topics
Examples of programs built using Modal
Python Dynamic Mode Decomposition