Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

scikit-learn: machine learning in Python

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…

Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

基于大模型搭建的聊天机器人，同时支持 微信公众号、企业微信应用、飞书、钉钉 等接入，可选择GPT3.5/GPT-4o/GPT-o1/ DeepSeek/Claude/文心一言/讯飞星火/通义千问/ Gemini/GLM-4/Claude/Kimi/LinkAI，能处理文本、语音和图片，访问操作系统和互联网，支持基于自有知识库进行定制企业智能客服。

My Python Examples

Datasets, Transforms and Models specific to Computer Vision

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

A framework to enable multimodal models to operate a computer.

A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

Scrape the Twitter Frontend API without authentication.

Collection of less popular features and tricks for the Python programming language

A library for scientific machine learning and physics-informed learning

A simple tool to update bib entries with their official information (e.g., DBLP or the ACL anthology).

Benchmark datasets, data loaders, and evaluators for graph machine learning

Awesome machine learning for combinatorial optimization papers.

CogDL: A Comprehensive Library for Graph Deep Learning (WWW 2023)

An Open-Source Package for Network Embedding (NE)

A Graph Neural Network Library in Jax

Computations and statistics on manifolds with geometric structures.

Topic modeling with latent Dirichlet allocation using Gibbs sampling

Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods

Some Conferences' accepted paper lists (including AI, ML, Robotic)

Riemannian Adaptive Optimization Methods with pytorch optim

Learning nonlinear operators via DeepONet

Self-labelling via simultaneous clustering and representation learning. (ICLR 2020)

A Unified Python Library for Graph Prompting

Module for statistical learning, with a particular emphasis on time-dependent modelling