machine-learning

A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.

A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.

This repository includes tutorials on how to use the TensorFlow estimator APIs to perform various ML tasks, in a systematic and standardised way

Automatic License Plate Recognition (ALPR) or Automatic Number Plate Recognition (ANPR) software that works with any camera.

News: the 10k dataset is ready for download.

A Python pickling decompiler and static analyzer

Processing and gridding spatial data, machine-learning style

MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.

Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.

Track your Data Science. Skore's open-source Python library accelerates ML model development with automated evaluation reports, smart methodological guidance, and comprehensive cross-validation analysis.

A-share quantitative system. A股量化系统

Blazing fast framework for fine-tuning similarity learning models

(AAAI' 20) A Python Toolbox for Machine Learning Model Combination

Gaussian processes in JAX and Equinox.

BanditPAM C++ implementation and Python package

CAIRI Supervised, Semi- and Self-Supervised Visual Representation Learning Toolbox and Benchmark

Quickly format your notes with ChatGPT in Obsidian

BenchMARL is a library for benchmarking Multi-Agent Reinforcement Learning (MARL). BenchMARL allows to quickly compare different MARL algorithms, tasks, and models while being systematically grounded in its two core tenets: reproducibility and standardization.

Awesome-LLM-Eval: a curated list of tools, datasets/benchmark, demos, leaderboard, papers, docs and models, mainly for Evaluation on LLMs. 一个由工具、基准/数据、演示、排行榜和大模型等组成的精选列表，主要面向基础大模型评测，旨在探求生成式AI的技术边界.

Code for the TCAV ML interpretability project

A repository of pretty cool datasets that I collected for network science and machine learning research.

Automatically split your PyTorch models on multiple GPUs for training & inference

Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.

Complete-Life-Cycle-of-a-Data-Science-Project

A simple and flexible code for Reservoir Computing architectures like Echo State Networks

A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.

A library to model multivariate data using copulas.

A reinforcement learning package for Julia

oneAPI Data Analytics Library (oneDAL)

MICA - Towards Metrical Reconstruction of Human Faces [ECCV2022]