Miaoyuanyuan777's Stars
dair-ai/ml-visuals
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
Lightning-AI/pytorch-lightning
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
shunliz/Machine-Learning
机器学习原理
jphall663/awesome-machine-learning-interpretability
A curated list of awesome responsible machine learning resources.
calico/scBasset
Sequence-based Modeling of single-cell ATAC-seq using Convolutional Neural Networks.
robbertliu/deeplearning.ai-andrewNG
deeplearning.ai , By Andrew Ng, All slide and notebook + data + solutions and video link
jackfrued/Python-100-Days
Python - 100天从新手到大师
d2l-ai/d2l-zh
《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
FunctionLab/ExPecto
predicting expression effects of human genome variants ab initio from sequence
scverse/scvi-tools
Deep probabilistic analysis of single-cell and spatial omics data
kimmo1019/EpiGePT
Geforme
wangprince2017/awosome-bioinformatics
A curated list of resources for learning bioinformatics.
MareesAT/GWA_tutorial
A comprehensive tutorial about GWAS and PRS
matplotlib/matplotlib
matplotlib: plotting with Python
scruel/Notes-ML-AndrewNg
Coursera吴恩达机器学习课程笔记及资源整理
GuanLab/Anchor
This is the package of Yuanfang's winning algorithm in the ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge
GuanLab/Leopard
jisraeli/DeepBind
Training and testing of DeepBind models.
TheisTrue/MLofAndrew-Ng
吴恩达机器学习课程的讲义,欢迎大家一起学习
tangyudi/Ai-Learn
人工智能学习路线图,整理近200个实战案例与项目,免费提供配套教材,零基础入门,就业实战!包括:Python,数学,机器学习,数据分析,深度学习,计算机视觉,自然语言处理,PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域
uci-cbcl/FactorNet
A deep learning package for predicting TF binding
dDipankar/DeepPTM
DeepPTM
QijinYin/DeepHistone
labmlai/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, ... 🧠
uci-cbcl/scFAN