1.Developer-Y / cs-video-courses
List of Computer Science courses with video lectures.
Ranked by Attention Score: stars gained over the last 7 complete days
26 repositories by Attention Score · Oct 27, 2026 – Nov 2, 2026 (UTC)
List of Computer Science courses with video lectures.
500 AI Machine learning Deep learning Computer vision NLP Projects with code
✅(已完结)超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】
Learn ML engineering for free in 4 months! Register here 👇🏼
邱锡鹏《神经网络与深度学习》第二版与通识版:电子书、章节目录、学习资源与勘误。
吴恩达老师的机器学习课程个人笔记
Free MLOps course from DataTalks.Club. Register here 👇🏼 to get notified about the next cohort
A curated list of awesome Deep Learning tutorials, projects and communities.
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
CVPR 2026 论文和开源项目合集
Quant/Algorithm trading resources with an emphasis on Machine Learning
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
🔥Highlighting the top ML papers every week.
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
A curated list of references for MLOps
A resource repository for 3D machine learning
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
Learn OpenCV : C++ and Python Examples
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
cvpr2024/cvpr2023/cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集,极市团队整理
:zap:机器学习实战(Python3):kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归
pytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
A curated list of resources for Document Understanding (DU) topic
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course