GitHub site for the book "Mathematical Methods in Data Science (with Python)" (soon to be published): mmids-textbook.github.io You can pre-order a print copy of the book here (with Amazon price guarantee): amzn.to/3KrbKvu
Understanding probability is essential in data science. In 4 minutes, I'll demolish your confusion. Let's go!
The math of LLMs is a fusion of three key areas: 1) Probability: They are massive statistical models that predict the next word based on the probability of what's come before. 2) Linear Algebra: All words and concepts are encoded as high-dimensional vectors (embeddings). The…
(Download 454-page PDF eBook) Introduction to Graph Theory: arxiv.org/abs/2308.04512 — edges, vertices, trees, networks, paths, and graphs (and theorems!) + Source for attached graphic: memgraph.com/blog/graph-alg… ————— #Mathematics #NetworkScience #DiscreteMath #GraphTheory
Last year, Sarthak (now at Princeton) did a directed reading project (DRP) under my guidance. Preparing these ordinary high-school children with pre-requisites to do such DRPs is the most difficult & demanding part of my mentorship. One such case is here sites.google.com/view/prasanna-….
"Introduction to Applied Linear Algebra" This book from Stanford University is available FREE. To get your copy, comment below.
Bayes Rules! — An Introduction to Applied Bayesian Modeling: amzn.to/3Qp0jo7 + Bayesian Modeling and Computation in #Python: amzn.to/3K15NQo ————— #Statistics #DataScience #Mathematics #Inference #ComputationalScience #Simulation #Probability #DataScientist
Gilbert Strang's "A Vision of Linear Algebra" Presents Professor Strang’s updated vision of how linear algebra could be taught. Youtube Playlist: youtube.com/playlist?list=… Course Website: ocw.mit.edu/courses/res-18…
At MIT, the only course I ever dropped was signal processing. The DFT math was too intimidating. It’s so easy to just type fft() in MATLAB and move on. Years later, I finally did DFT by hand. ✍️ If you are also afraid of DFT, I hope this helps! ⬇️ Download:…
Model-Based Clustering and Classification for #DataScience, with Applications in R: amzn.to/4aV1VhH ————— #Rstats #DataScientist #MachineLearning #ML #AI #Statistics #Mathematics
#Probability and #Statistics Essentials for #DataScience and #MachineLearning, with 200+ examples and pictures [Kindle Edition]: amzn.to/43a7tmo
![KirkDBorne's tweet image. #Probability and #Statistics Essentials for #DataScience and #MachineLearning, with 200+ examples and pictures [Kindle Edition]: amzn.to/43a7tmo](https://pbs.twimg.com/media/G21p2ZMXYAAip9n.jpg)
Must-read excellent books with 🆓 PDF available to download from the author/book web pages
11 FREE Books from MIT for Absolute Beginners - Machine Learning (ML) - Deep Learning (DL) - Reinforcement Learning (RL) - Artificial Intelligence (AI) To get: - 1. Follow (So I can DM you ) 2. Like & retweet 3. Reply " Send "
Michigan's "Robotics 501: Mathematics for Robotics" 📽️ Lecture Videos: youtube.com/playlist?list=… 📷 Github: github.com/michiganroboti…
Stanford is offering Deep Learning course for FREE! Instructor: Andrew Ng Launched on: September 23, 2025 Find the first lecture video in the 🧵👇
I tested 12 AI writing tools for academic papers. Only 5 passed journal editorial standards. Here's what editors actually accept (and what gets you rejected):
We're about to create the 1st gen of scientists who can't research without AI. And honestly? I'm not sure if that's evolution or devolution! 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀 𝗮𝗿𝗲 𝗻𝗼𝘄 𝘂𝘀𝗶𝗻𝗴 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝘁𝗼: — Extract key findings from dense papers in seconds — Design entire…
Mathematical Theory of #DeepLearning [download 282-page PDF]: arxiv.org/abs/2407.18384 + + See also this book: amzn.to/3BqaW5e ————— #AI #DataScience #ML #MachineLearning #Calculus #DataScientist #Mathematics #Algorithms
![KirkDBorne's tweet image. Mathematical Theory of #DeepLearning [download 282-page PDF]: arxiv.org/abs/2407.18384
+ +
See also this book: amzn.to/3BqaW5e
—————
#AI #DataScience #ML #MachineLearning #Calculus #DataScientist #Mathematics #Algorithms](https://pbs.twimg.com/media/G2JphOzXQAAkc_t.jpg)
Download 649-page PDF >> Introduction to Machine Learning (textbook on foundations, algorithms, and techniques): arxiv.org/abs/2409.02668 #MachineLearning #DeepLearning #Mathematics #DataScience #DataScientist
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