Nanci
@Nanci_Baygorrea
Associate professor at #UENF. Passionate about #AI 🇧🇷 🇵🇪 #PhD #math #RJ #UFRJ #CETEM #python #life #free #MachineLearning
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"An Introduction to Statistical Learning" Book freely available at: statlearning.com Youtube Playlist (Python version): youtube.com/playlist?list=… Youtube Playlist (R version): youtube.com/playlist?list=…
Yeees, the 2025 Topological Deep Learning Challenge is already here! 🏆 This 3rd edition, join us in expanding the TDL data landscape and compete for 💰 cash prizes & 🌟 exciting internships! 📄 Guidelines & details: geometric-intelligence.github.io/topobench/tdl-…
MIT Courses on AI & ML (ALL FREE): ❯ 6.034 : Artificial Intelligence ❯ 6.036 : Machine Learning ❯ 6.S191 : Deep Learning ❯ 18.06 : Linear Algebra ❯ 18.05 : Probability and Statistics ❯ 18.S096 : Matrix Calculus Links inside:
Microsoft has one of the best free generative AI courses you'll find. Save this for later.
🤯This Deep Learning Playlist has one of the best animations. Link in comment 33 videos covering everything from backpropagation to coding your own transformer from scratch in PyTorch.
MIT literally packed 7 hours with everything you need to know about Gen AI for free
"Introduction to Machine Learning Systems" - FREE from MIT Press - Authored by Harvard Professor - 2048 Pages
In the 20th century, non-Euclidean geometry transformed how we model the world with pen&paper. Now, it disrupts how we model the world w machines👇 @mathildepapillo @naturecomputes @johmathe @louisacornelis @AbbyBertics Buracas @hansenlillemark @cashewmake2 @fatihdin4en Pennec
Our illustrated guide to non-Euclidian ML is finally published! Check it out for ⭐️ gorgeous figures (with new additions!) on topology, algebra, and geometry in the field ⭐️ broken down tables for easy reading ⭐️ accessible text, additional refs, and more iopscience.iop.org/article/10.108…
New 20hr bootcamp on Probability & Statistics!!! Videos released weekly but full playlist already posted: youtube.com/watch?v=sQqnia… Probability & Statistics are cornerstones of data science and machine learning. This course rapidly covers the basics and gets into advanced topics.
You don't need to know programming or GIS to use geospatial data. Here are 4 resources to get you started:
📢 I am teaching an Introduction to GIS Programming course this semester! All course materials are freely available online. New video lectures will be uploaded twice a week. Check out the links below to learn #geospatial 🌍 data visualization and analysis using #opensource Python…
The Top ML Papers of the Week (August 19 - 25): - GraphRAG Methods - LLMs for Tabular Data - Automated Agentic Systems - Enhancing Robustness in LLMs - Controllable Text Generation for LLMs - LLM Pruning and Distillation in Practice ...
How to map your research article efficiently
A mindmap for PhD students struggling with their thesis structure
Curated list of many great CS/IT/ML/AI books with links to free PDFs provided by the Authors: Check the list at: 👉tinyurl.com/CuratedBL
Want to build real applications—not just toys—with LLMs? Then you need to take our free LLMOps course! Taught by Elvis Saravia, it will teach you everything you need to get started building production-scale LLM applications.
Visualizing Bregman divergences vs visualizing equivalent Fenchel-Young divergences arxiv.org/abs/2202.10726
🚀 Here comes a Deep Graph Generation survey paper: “A Survey on Deep Graph Generation: Methods and Applications.” It comprehensively reviews everything about Deep Graph Generation, from the absolute basics to trend technologies. Paper: proceedings.mlr.press/v198/zhu22a.ht…
Data often exhibit non-Euclidean structure: From the curvature of space-time🌐, to topologically complex interactions between neurons🍩, to algebraic transformations describing symmetries in physical systems💎. How can ML/AI best process this data? Check out our new review!
I continue to be alarmed at the progress of proposed California regulation SB 1047 and the attack it represents on open source and more broadly on AI innovation. As I wrote previously, this proposed law makes a fundamental mistake of regulating AI technology instead of AI…
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