BGM's repositories
AI4Science101
AI for Science
annotated_deep_learning_paper_implementations
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
awesome-ai-bioinformatics
A curated list of awesome AI and Bioinformatics.
Awesome-Bio-Foundation-Models
A collection of awesome bio-foundation models, including protein, RNA, DNA, gene, single-cell, and so on.
awesome-deep-learning-4-life-sciences
A collection of resources for Deep Learning in Python for Life Sciences (with focus on biotech and pharma).
awesome-graph-representation-learning
A curated list for awesome graph representation learning resources.
Awesome-LLM-KG
Awesome papers about unifying LLMs and KGs
awesome-transformers-in-medical-imaging
A collection of resources on applications of Transformers in Medical Imaging.
cpython
The Python programming language
generative-ai-for-beginners
12 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
Genome_Fine-Tuning
Pre-trained models applied to genomic tasks
Graphormer
Graphormer is a deep learning package that allows researchers and developers to train custom models for molecule modeling tasks. It aims to accelerate the research and application in AI for molecule science, such as material design, drug discovery, etc.
hf-nlp-book
基于 Hugging Face NLP 课程的中文书籍协作。
hugging-llm
HuggingLLM, Hugging Future.
hyena-dna
Official implementation for HyenaDNA, a long-range genomic foundation model built with Hyena
kg-covid-19
An instance of KG Hub to produce a knowledge graph for COVID-19 response.
llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
mathematical-modeling
python数学实验与建模（详细安装，知识点总结，书中程序及数据），司守奎版
NLP4SciencePapers
Must-read papers on NLP for science.
nndl.github.io
《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning
torchkeras
Pytorch❤️ Keras 😋😋
Transformers-for-NLP-2nd-Edition
Transformer models from BERT to GPT-4, environments from Hugging Face to OpenAI. Fine-tuning, training, and prompt engineering examples. A bonus section with ChatGPT, GPT-3.5-turbo, GPT-4, and DALL-E including jump starting GPT-4, speech-to-text, text-to-speech, text to image generation with DALL-E, Google Cloud AI,HuggingGPT, and more