MathProgThink @mathprogthink
Mathematician, Programmer, Thinker Joined May 2022-
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🔥FREE Google Colab notebooks to implement every Machine Learning Model from Scratch. Link in comment.
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MathProgThink retweeted
Top 15 Tools for Researchers 𝟏. 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐏𝐚𝐩𝐞𝐫 𝐖𝐫𝐢𝐭𝐢𝐧𝐠 ➝ @answerthisio: Helps you write papers 10x faster and much better ➝ @teampaperpal: Offers more than 10 features for writing papers ➝ @SciSummary: Compares research papers to identify research gap…
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How to cut your PhD research time by a third with 35 tools most PhDs don't know about Most PhD students use ChatGPT and Google Scholar. That's like using a bicycle on a highway. Smart researchers use specialized tools for each task 🧵
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Correlation is the skill that has singlehandedly benefitted me the most in my career. In 3 minutes I'll demolish your confusion (and share strengths and weaknesses you might be missing). Let's go:
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Data Structures and Algorithm Analysis by Mark Allen Weiss archive link: archive.org/details/datast…
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🔥Free Google Collab notebooks to implement every Machine Learning Algorithm from scratch Link in comment
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Michigan's "Robotics 101: Computational Linear Algebra" 📽️ Lecture Videos: youtube.com/playlist?list=… 📷 Github: github.com/michiganroboti… (audio generated by NotebookLM)
MathProgThink retweeted
Understanding probability is essential in data science. In 4 minutes, I'll demolish your confusion. Let's go!
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Combine MATLAB and Python in your AI workflows. Learn how to convert models and run both together. Download the guide: spr.ly/6019fKoJd #AI #Python #MATLAB #MachineLearning
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Harvard's "Linear Algebra with Probability" by Oliver Knill PDF:people.math.harvard.edu/~knill/teachin… (audio generated by NotebookLM)
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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
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The Art of Statistics:
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MIT's "Matrix Calculus for Machine Learning" Lecture Notes: ocw.mit.edu/courses/18-s09… Video: youtube.com/playlist?list=… audio generated by notebookLM
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40 NumPy methods used 95% of the time:
MathProgThink retweeted
🚀 Just read "Symbolic Regression with Multimodal LLMs and Kolmogorov–Arnold Networks" (arXiv: 2505.07956) — and wow. LLMs take a function plot, suggest symbolic expressions, and a KAN breaks down multivariate functions into interpretable pieces. The result?
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