MIT: Papers + Code

0 stars0 forks0 contributors

Overview

"Peer-review is the lifeblood of scientific validation and a guardrail against runaway hype in AI. Our commitment to publishing in the top venues reflects our grounding in what is real, reproducible, and truly innovative."

Related Projects

Community-curated · Updated weekly · 100% open source

Found a gem we're missing?

Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.

Submit a project Star on GitHub

Last commit

Created

Links & Resources

Website

Included in

Dive into Machine Learning11.4k

"most important thing in data science is the question"

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

Stars4,117

Forks30,994

Last commit5 years ago

"Advice on building a machine learning career and reading research papers by Prof. Andrew Ng"

, it works great for some folks. (Don't pressure yourself yet though! Everybody is different, and it's good to know your learning style.)

Stars0

Forks0

Last commit

papers.labml.ai/papers/weekly

, monthly

Stars0

Forks0

Last commit