links to conference publications in graph-based deep learning
- graph-neural-networks
- graph-convolutional-networks
- graph
- deep-learning
Repository Index
77,852 visible repositories in the index
265–288 of 1,002 · Most stars
https://hrl.boyuai.com/
Translated🎓 Academic portfolio that boosts citations. AI generates pages, you own as Markdown. BibTeX auto-import, Jupyter, LaTeX, slides, visual block editor — free to host forever. Academic homepage, AI-generated, Markdown-owned 👇
- hugo
- website-generation
- academic
- netlify
Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
- dependency-graph
The "Python Machine Learning (3rd edition)" book code repository
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
TranslatedSome interesting Python crawlers and data analysis projects
Learn python3 in one picture.
unet for image segmentation
- unet
- keras
- segmentation
A Bulletproof Way to Generate Structured JSON from Language Models
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
Translated"Deep Learning from Scratch" (O'Reilly Japan, 2016)
The 3rd edition of course.fast.ai
- data-science
- fastai
- deep-learning
- pytorch
🚀 An open-source, hands-on curriculum bridging the gap from basic RL concepts to LLM alignment, RLVR, and advanced Agentic systems.
- agent
- agentic
- agentic-ai
- agentic-rl
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
- machine-learning
- dockerfiles
- jetson
- pytorch
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
- machine-learning
- economics
- causal-inference
- causality
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
- bayesian-methods
- deep-learning
- machine-learning
- data-science
Jupyter notebooks for the Natural Language Processing with Transformers book
A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
- data-science
- machine-learning
- deep-learning
- data-portfolio
TranslatedKnowledge, code, and ideas for data mining, computer vision, natural language processing, and recommender system competitions
- kaggle
- data-competition
- data-science
- deep-learning
Acceptance rates for the major AI conferences
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
- reinforcement-learning
- machine-learning
- artificial-intelligence
- deep-reinforcement-learning
🔥 LeetCode for PyTorch — practice implementing softmax, attention, GPT-2 and more from scratch with instant auto-grading. Jupyter-based, self-hosted or try online.
35 production-grade agentic AI architectures (Reflexion, LATS, GraphRAG, MemGPT, Voyager, BrowserAgent, ...) — a Python library and runnable textbook with multi-provider LLM support and a 17-task benchmark leaderboard.
- agentic-ai
- ai-agents
- langchain
- langgraph