machine-learning

Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.

Linear Prediction Model with Automated Feature Engineering and Selection Capabilities

Awesome machine learning model compression research papers, quantization, tools, and learning material.

Next-generation Albumentations: dual-licensed for open-source and commercial use

OWASP CycloneDX is a full-stack Bill of Materials (BOM) standard that provides advanced supply chain capabilities for cyber risk reduction. SBOM, SaaSBOM, HBOM, AI/ML-BOM, CBOM, OBOM, MBOM, VDR, and VEX

Awesome papers on Language-Model-as-a-Service (LMaaS)

High-quality and streaming Speech-to-Speech interactive agent in a single file. 只用一个文件实现的流式全双工语音交互原型智能体！

Cleora AI is a general-purpose open-source model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data. Created by Synerise.com team.

Your no-nonsense guide to the Math used in Artificial Intelligence

A simple & elegant experiment tracking framework that integrates persistence logic & best practices directly into Python

Build a chatbot or Q&A bot of your website's content

A set of tools to use in Microsoft Azure Form Recognizer and OCR services.

Audio samples accompanying publications related to Tacotron, an end-to-end speech synthesis model.

Machine Learning library for the web and Node.

CodaLab Competitions

Confusion Matrix in Python: plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib

A PyTorch implementation of Perceiver, Perceiver IO and Perceiver AR with PyTorch Lightning scripts for distributed training

This repository is for all those AI enthusiastics who actually loves to read books and learn.

Distributed Machine Learning Patterns from Manning Publications by Yuan Tang https://bit.ly/2RKv8Zo

apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly. See the documentation page: https://apricot-select.readthedocs.io/en/latest/index.html

A collection of data science and machine learning resources that I've found helpful (I only post what I've read!)

Curated list of publicly accessible machine learning engineering courses from CalTech, Columbia, Berkeley, MIT, and Stanford.

Explore and interpret large embeddings in your browser with interactive visualization! 📍

Curated list of awesome papers and resources in quantum machine learning

How ready is Rust for Machine Learning?

Run your deep learning workloads on Kubernetes more easily and efficiently.

A simple python OCR engine using opencv

Human-explainable AI.

Neural Amp Modeler LV2 plugin

TensorLayerX: A Unified Deep Learning and Reinforcement Learning Framework for All Hardwares, Backends and OS.