jimsimonsfan @00pium_math
Currently grinding deep learning from scratch Joined March 2020-
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In recent times, I’ve noticed a significant increase in applications [at AMMOC] from high-school students in Eastern Europe who show a strong interest and talent in pursuing careers in the foundational and philosophical aspects of theoretical mathematics. 1/2.
Video lectures, UC Berkeley CS 168 Introduction to the Internet: Architecture and Protocols summer 2025, by Peyrin Kao, Tess Despres su25.cs168.io
hypothetical two-year degree in AI: - Coding in Python - Semiconductors 101 - Intro to machine learning - Intro to data science - Data visualization & dimensionality reduction - Machine learning engineering - Language models - Deep learning (basics & architectures) -…
Video lectures, Toronto ECE 1508 Deep Generative Models summer 2025, by Ali Bereyhi bereyhi-courses.github.io/genai-utoronto… bereyhi-courses.github.io/genai-utoronto…
10 GitHub repos to sleep with as an ai engineer covering ML systems, Agents, RAG, MLOps: 1. Machine Learning for Beginners by Microsoft → Start here if you’re brand new to ML. Covers basic ML concepts in Jupyter notebooks beginner-friendly and visual. 🔗 lnkd.in/gGithBVP…
become a self-taught ml engineer i published this blog yesterday, a year ago -- 8.9k reads to date. i'm pretty excited that my alma mater invited me to give a talk on this tomorrow (link to blog in comments)
Wrapped up Stanford CS336 (Language Models from Scratch), taught with an amazing team @tatsu_hashimoto @marcelroed @neilbband @rckpudi. Researchers are becoming detached from the technical details of how LMs work. In CS336, we try to fix that by having students build everything:
how to get hired @xai to work on kernel by end of summer grok.com/share/bGVnYWN5…
Link: peterbloem.nl/blog/transform… By: Peter Bloem
DSA is asked in almost every place. If you can do at least leetcode medium by yourself without any hints, then you can clear most company's DSA round. If u haven't done DSA, then you can speed run the InterviewBit problem set (contains ~270 qsns). interviewbit.com/courses/progra… (2/11)
I said once that I have been here for quite a long time since early 2023, but was quite observer and learner. One of the accounts I found was @shivambhadani_ His roadmap is where am I today. Its time tech community has the treasure/legacy once he held Ultimate thread 🧵-
I have used them both for courses on analysis for Nihad Hashimov, Keisha Kwok, and Medha. The first one is preferred over Terry Tqo (MY FAVOURITE) and D G H Garling (Cambridge) IF you want to cover core topics of a first course in mathematical analysis WITHIN 3 MONTHS.
LECTURE NOTES ON PROBABILITY, STATISTICS AND LINEAR ALGEBRA by C. H. Taubes people.math.harvard.edu/~knill/teachin…
Video lectures, UC Berkeley CS 189 / 289A Introduction to Machine Learning spring 2025, by Jonathan Shewchuk people.eecs.berkeley.edu/~jrs/189/
i actually didn’t know o’reilly had such a dope book that explains deep learning from first principles in Python. you can learn from scratch algos like: > chain rule and derivatives > neural nets from scratch > trainer and optimizer > dropout and softmax > CNN and RNN
Oxford's "Introduction to University Mathematics" Lecture notes, videos, and more: courses.maths.ox.ac.uk/course/view.ph…
UC Berkeley's "Introduction to Mathematical Thinking" Lecture videos & slides: imt-decal.org
I am pleased to share the full set of videolectures, slides, textbook, and other supporting material of the 7th offering of my Reinforcement Learning class at ASU, which was completed two days ago; check web.mit.edu/dimitrib/www/R…
My course lecture on Diffusion Models from statistical first principles: dropbox.com/scl/fi/gmwhx7j… The PyTorch notebooks that implement Diffusion Models from scratch w/ Transformer and UNet: github.com/xbresson/CS524…

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