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"Pen and Paper Exercises" in Machine Learning 211 Pages. 75+ Exercises w/ solutions. Comment to receive a FREE copy.
Stanford's "Applied Matrix Theory" Class notes (2008): PDF: candes.su.domains/teaching/math1…
Multivariate interpolation estimates unknown values based on multiple variables, making it useful in physics, finance, and machine learning. It allows for smoother approximations and more accurate predictions in multidimensional spaces. Common methods include bilinear, bicubic,…
𝗧𝗼𝗽 𝗔𝗜 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀 & 𝗧𝗵𝗲𝗶𝗿 𝗨𝘀𝗲-𝗖𝗮𝘀𝗲𝘀
Download 242-page PDF “Introduction to #NeuralNetworks” ➡️ dkriesel.com/en/science/neu… ————— #DataScience #AI #Algorithms #ML #MachineLearning #DeepLearning #Mathematics #Calculus #DataScientist
MIT's "Statistics for Applications" Lecture Videos: youtube.com/playlist?list=… Lecture Slides: ocw.mit.edu/courses/18-650…
"Foundations of Machine Learning" A MUST for learning AI/ML. Absolutely Beginner friendly. Do you want to read it FREE?
[Updated 737-page PDF eBook] Mathematical Introduction to #DeepLearning — Methods, Implementations, and Theory: arxiv.org/abs/2310.20360 ———— #AI #Mathematics #DataScience #Algorithms #ML #MachineLearning #Calculus #LinearAlgebra #DataScientist
![KirkDBorne's tweet image. [Updated 737-page PDF eBook]
Mathematical Introduction to #DeepLearning — Methods, Implementations, and Theory: arxiv.org/abs/2310.20360
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[Download 309-page PDF eBook] "Patterns, Predictions, and Actions: A Story About #MachineLearning" at arxiv.org/abs/2102.05242 …sharpen your #Probability, #Calculus, and #LinearAlgebra knowledge with this! ————— #DataScience #AI #DeepLearning #ML #DataScientist #Mathematics
![KirkDBorne's tweet image. [Download 309-page PDF eBook] "Patterns, Predictions, and Actions: A Story About #MachineLearning" at arxiv.org/abs/2102.05242
…sharpen your #Probability, #Calculus, and #LinearAlgebra knowledge with this!
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Understanding P-Values is essential for improving regression models. In 2 minutes, I'll crush your confusion.
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
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