从 65,744 个高星开源项目里，
找到你要的下一个。

imgcook 是一个学习资料，用于系统学习与查阅。

Generate pages from any sketch or images.

CoreML-Models 是用 Swift 编写的学习资料，用于系统学习与查阅。

Core ML model zoo for iOS/macOS — PyTorch models converted to ready-to-use .mlpackage, each with a conversion script and SwiftUI sample app. Sibling…

surpriver 是用 Python 编写的交易类项目，用于商城、支付与交易场景。

Find big moving stocks before they move using machine learning and anomaly detection

intelligent-trading-bot 是用 Python 编写的交易类项目，用于商城、支付与交易场景。

Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering

pyts 是用 Python 编写的学习资料，用于系统学习与查阅。

A Python package for time series classification

alan-sdk-ios 是用 Objective-C 编写的学习资料，用于系统学习与查阅。

The Self-Coding System for Your App — Alan AI SDK for iOS

tensorflow_template_application 是用 Python 编写的学习资料，用于系统学习与查阅。

TensorFlow template application for deep learning

sonar 是用 Python 编写的 AI 工具，用于人工智能方向的建模与推理。

Large-scale LLM inference engine

automl-gs 是用 Python 编写的学习资料，用于系统学习与查阅。

Provide an input CSV and a target field to predict, generate a model + code to run it.

llm-applications 是用 Jupyter Notebook 编写的学习资料，用于系统学习与查阅，主打功能完整。

A comprehensive guide to building RAG-based LLM applications for production.

dpm-solver 是用 Python 编写的 AI 工具，用于人工智能方向的建模与推理，主打速度快。

Official code for "DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps" (Neurips 2022 Oral)

AI-Blocks 是用 JavaScript 编写的 AI 工具，用于人工智能方向的建模与推理，主打功能完整。

A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!

awesome-embedding-models 是用 Jupyter Notebook 编写的资源清单，按主题汇总同类优质资源。

A curated list of awesome embedding models tutorials, projects and communities.

awesome-semi-supervised-learning 是一个 AI 工具，用于人工智能方向的建模与推理。

😎 An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.

Gen.jl 是用 Julia 编写的 AI 工具，用于人工智能方向的建模与推理。

A general-purpose probabilistic programming system with programmable inference

spago 是用 Go 编写的学习资料，用于系统学习与查阅。

Self-contained Machine Learning and Natural Language Processing library in Go

AB3DMOT 是用 Python 编写的 AI 工具，用于人工智能方向的建模与推理。

(IROS 2020, ECCVW 2020) Official Python Implementation for "3D Multi-Object Tracking: A Baseline and New Evaluation Metrics"

data-science-complete-tutorial 是用 Jupyter Notebook 编写的学习资料，用于系统学习与查阅。

For extensive instructor led learning

machine-learning-experiments 是用 Jupyter Notebook 编写的 AI 工具，用于人工智能方向的建模与推理。

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

byzer-lang 是用 Scala 编写的学习资料，用于系统学习与查阅，主打开源免费。

Byzer (former MLSQL): A low-code open-source programming language for data pipeline, analytics and AI.

awesome-AI-books 是用 Jupyter Notebook 编写的学习资料，用于系统学习与查阅。

Some awesome AI related books and pdfs for learning and downloading, also apply some playground models for learning

magenta-realtime 是用 Python 编写的学习资料，用于系统学习与查阅。

Magenta RealTime 2: An Open-Weights Live Music Model

RustQuant 是用 Rust 编写的学习资料，用于系统学习与查阅。

Rust library for quantitative finance.

Awesome-Deep-Learning-Resources 是一个资源清单，按主题汇总同类优质资源。

Rough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there…