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csinva.github.io
Slides, paper notes, class notes, blog posts, and research on ML 📉, statistics 📊, and AI 🤖.
Stars: 573
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csinva.github.io is a repository maintained by Chandan, a Senior Researcher at Microsoft Research, focusing on interpretable machine learning. The repository contains slides, research overviews, cheat sheets, notes, blog posts, and personal information related to machine learning, statistics, and neuroscience. It offers resources for presentations, summaries of recent papers, cheat sheets for various courses, and posts on different aspects of machine learning and neuroscience advancements.
README:
Hi 👋 I'm Chandan, a Senior Researcher at Microsoft Research working on interpretable machine learning. I've been compulsively taking / improving my notes since my PhD at UC Berkeley and share them on this website. Hope they're helpful :)
Slides •
Research overviews •
Cheat sheets •
Notes
Blog posts •
Personal info
@csinva
The pres folder contains source for presentations, including ML slides from teaching machine learning at berkeley
The source is in markdown (built with reveal-md) and is easily editable / exportableThe research_ovws folder contains overviews and summaries of recent papers in different research areas
The _notes folder contains markdown notes and cheat-sheets for many different courses and areas between computer science, statistics, and neuroscience
Posts on various aspects of machine learning / statistics / neuroscience advancements (some selected posts below)
- paper writing tips(2023)
- forecasting paper titles (2022)
- imodels (2022, bairblog)
- For updates, star the repo or follow @csinva
- Feel free to use openly!
- Built with jekyll | github pages | timeline theme | particles.js | jupyterbook
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csinva.github.io
csinva.github.io is a repository maintained by Chandan, a Senior Researcher at Microsoft Research, focusing on interpretable machine learning. The repository contains slides, research overviews, cheat sheets, notes, blog posts, and personal information related to machine learning, statistics, and neuroscience. It offers resources for presentations, summaries of recent papers, cheat sheets for various courses, and posts on different aspects of machine learning and neuroscience advancements.
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