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🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
Up-to-date version of labs for ISLP
well-documented demonstration Python Jupyter workflows for many common machine learning workflows
📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Bayesian optimisation & Reinforcement Learning library developed by Huawei Noah's Ark Lab
Repository for benchmarking graph neural networks (JMLR 2023)
Official implementation code of the paper <AnyText: Multilingual Visual Text Generation And Editing>
A Python package for processing molecules with RDKit in scikit-learn
Experimental design and (multi-objective) bayesian optimization.
Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现
Collection of AI-related utilities. Welcome to submit issues and pull requests /收藏AI相关的实用工具，欢迎提交issues 或者pull requests
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
🔥Highlighting the top ML papers every week.
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
⚡ TabPFN: Foundation Model for Tabular Data ⚡
This repo includes Claude prompt curation to use Claude better.
Official implementation of SketchMol.
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
A powerful and flexible machine learning platform for drug discovery
DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules…
Book about interpretable machine learning
links to conference publications in graph-based deep learning
