CodeRayZhang/Deep-Learning-Papers-Reading-Roadmap

深度学习论文阅读路线图

42
/ 100
Emerging

This is a curated collection of foundational and influential academic papers in deep learning, organized by historical breakthroughs and methodological advancements. It takes a list of key deep learning concepts and provides the corresponding research papers. This resource is invaluable for researchers, students, and practitioners in artificial intelligence who want to understand the origins and evolution of deep learning.

329 stars. No commits in the last 6 months.

Use this if you are an AI researcher, a graduate student in machine learning, or a deep learning practitioner who wants to delve into the seminal papers that shaped the field.

Not ideal if you are looking for practical code implementations, tutorials for building deep learning models, or a high-level overview of deep learning applications.

Artificial Intelligence Research Machine Learning Education Deep Learning History Academic Literature Review Neural Networks Theory
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 24 / 25

How are scores calculated?

Stars

329

Forks

91

Language

License

Last pushed

Feb 13, 2018

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/CodeRayZhang/Deep-Learning-Papers-Reading-Roadmap"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.