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Qin Liang's Projects

annotated_deep_learning_paper_implementations icon annotated_deep_learning_paper_implementations

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

az303 icon az303

Azure AZ-303 Microsoft Azure Architect Technologies Crash Course

az304 icon az304

Exam AZ-304 - Microsoft Azure Architect Design Crash Course

book icon book

关于技术类的电子书,为了去中心化,保存在git上,不至于丢失,[侵删]

cmwtat_digital_edition icon cmwtat_digital_edition

CloudMoe Windows 10 Activation Toolkit get digital license, the best open source Win 10 activator in GitHub. GitHub 上最棒的开源 Win10 数字权利(数字许可证)激活工具!

cs-base icon cs-base

图解计算机网络、操作系统、计算机组成、数据库,共 1000 张图 + 50 万字,破除晦涩难懂的计算机基础知识,让天下没有难懂的八股文!🚀 在线阅读:https://xiaolincoding.com

dash-recipes icon dash-recipes

A collection of scripts and examples created while answering questions from the greater Dash community

deepfacelab icon deepfacelab

DeepFaceLab is the leading software for creating deepfakes.

dive-into-dl-pytorch icon dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

easy-rl icon easy-rl

强化学习中文教程(蘑菇书),在线阅读地址:https://datawhalechina.github.io/easy-rl/

elegantrl icon elegantrl

Massively Parallel Deep Reinforcement Learning. 🔥

face_recognition icon face_recognition

The world's simplest facial recognition api for Python and the command line

fashion-mnist icon fashion-mnist

A MNIST-like fashion product database. Benchmark :point_right:

getting-things-done-with-pytorch icon getting-things-done-with-pytorch

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network,

hellinger-montecarlo icon hellinger-montecarlo

Monte Carlo Approximation of a Hellinger Distance between Categorical Distributions Using Non-Exchangeable Data

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