Stars
I have surveyed the technology and papers of CTR & Recommender System, and implemented 25 common-used models with Pytorch for reusage. （对工业界学术界的CTR推荐调研并实现25个算法模型，2023）
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
A script for checking availability of GPUs and runs your scripts during peak times
DSMIL: Dual-stream multiple instance learning networks for tumor detection in Whole Slide Image
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slides, BCNB Dataset
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Implementing Logistic Regression on MNIST dataset from scratch
常见数据结构与算法的Python实现及学习笔记
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
An opinionated list of awesome Python frameworks, libraries, software and resources.
主要存储Datawhale组队学习中“数据挖掘/机器学习”方向的资料。