Juncheng2021's Stars
hyperai/tvm-cn
TVM Documentation in Chinese Simplified / TVM 中文文档
vllm-project/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
0voice/cpp_new_features
2021年最新整理， C++ 学习资料，含C++ 11 / 14 / 17 / 20 / 23 新特性、入门教程、推荐书籍、优质文章、学习笔记、教学视频等
yuanxiaosc/Find-a-Machine-Learning-Job
找一份机器学习工作（算法工程师），需要提纲（算法能力）挈领（编程能力），充分准备。 本人学习和在找工作期间受到了很多前辈们的帮助，目前已经找到心仪的工作，撰写此文献给那些在求职路上有梦有汗水的人们！2020秋招算法，难度剧增！没有选择，只能迎难而上。
zhengjingwei/machine-learning-interview
算法工程师-机器学习面试题总结
amusi/AI-Job-Notes
AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）
Hirqs/PiLiBaLa
PKUanonym/REKCARC-TSC-UHT
清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University
QSCTech/zju-icicles
浙江大学课程攻略共享计划
Megvii-BaseDetection/YOLOX
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
UoS-EEC/DynamicOFA
[CVPRW 2021] Dynamic-OFA: Runtime DNN Architecture Switching for Performance Scaling on Heterogeneous Embedded Platforms
computing-intelligence/ai-edu
AI education materials for Chinese students, teachers and IT professionals.
microsoft/AutonomousDrivingCookbook
Scenarios, tutorials and demos for Autonomous Driving
youngyangyang04/leetcode-master
《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀
imarvinle/awesome-cs-books
🔥 经典编程书籍大全，涵盖：计算机系统与网络、系统架构、算法与数据结构、前端开发、后端开发、移动开发、数据库、测试、项目与团队、程序员职业修炼、求职面试等
yuishihara/chainer-naf
Reproduction code of Continuous Deep Q-Learning with Model-based Acceleration
carpedm20/NAF-tensorflow
"Continuous Deep Q-Learning with Model-based Acceleration" in TensorFlow
SmileOfHeart/xgboostTrain_accuracyStop
基于Xgboost算法的列车节能控制 Subway Train Energy Saving Control Based on Xgboost Algorithm
thu-ml/tianshou
An elegant PyTorch deep reinforcement learning library.
ray-project/ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
alessandrostockman/rl-flatland
Reinforcement Learning solution for a vehicle scheduling problem proposed by the Swiss Federal Railway Company
SmileOfHeart/SubwayOperationCoastControl
optimization for traction energy of Subway train using GA
SmileOfHeart/TrainControlOptimation
Optimal for traction energy consumption of subway by different Algorithm
MisterBooo/hello-offer
图解剑指 Offer，迎接秋招，找到好工作。
matlab-deep-learning/rl-agent-based-traffic-control
Develop agent-based traffic management system by model-free reinforcement learning
MorvanZhou/Tensorflow-Tutorial
Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学
Farama-Foundation/HighwayEnv
A minimalist environment for decision-making in autonomous driving
MorvanZhou/Reinforcement-learning-with-tensorflow
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
ml-tooling/best-of-ml-python
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
anantvignesh/Training-Self-Driving-Car-Using-Reinforcement-Learning
It is highly evident that autonomous vehicles will be the future and it will be a prominent vehicle category in the next decade. For this to be a success, the vehicle should be safe, reliable and provide a comfortable user experience. Autonomous driving must have sophisticated negotiating skills while taking right, left turns and while pushing ahead in urban areas. Reinforcement learning is considered as the main domain for learning driving policy. We propose a reinforcement learning approach using deep Q-learning approach which will extract the maximum reward from a large state space. We use CARLA, an open-source simulator for autonomous driving research. The outcome of this experiment is to resemble a real-life environment where the agent tries to overcome the obstacles using the data from the virtual sensors attached to the agent.