6 ms·

There are many others that are better. 1/ The Annotated Transformer Attention is All You Need http://nlp.seas.harvard.edu/annotated-transformer/ http://nlp.sea

• rvnx 2y ago
  In addition, these websites are totally free. The website listed here: > I consider requests for full commercial use of all content on this site (and the github repository). For a complete buyout of all content rights, the cost is €10,000,000. > I’d like to ask you what problems you have by that I keep on having the copyright of my document. + no commercial-use without paying 20% royalty. So fairly expensive for a Keras tutorial.
  • bitmaks 2y ago
    I think that's pretty obviously a joke, no?
• mr_puzzled 2y ago
  Slightly off topic: I'm interested in taking part in the Vesuvius challenge[0], but I don't have a background in ML, just a regular web developer. Does anyone have suggestions on how to get started? I planned to get some background on practical ML by working through Karpathy's Zero to Hero series along with the Understanding Deep Learning book. Would that be enough or anything else I should learn? I plan to understand the existing solutions to last year's prize and then pick a smaller sub challenge. [0] https://scrollprize.org/ https://scrollprize.org/
  • trybackprop 2y ago
    I made a list of all the free resources I used to study ML and deep learning to become an ML engineer at FAANG, so I think it'll be helpful to follow these resources: https://www.trybackprop.com/blog/top_ml_learning_resources https://www.trybackprop.com/blog/top_ml_learning_resources (links in the blog post) Fundamentals Linear Algebra – 3Blue1Brown's Essence of Linear Algebra series, binged all these videos on a one hour train ride visiting my parents Multivariable Calculus – Khan Academy's Multivariable Calculus lessons were a great refresher of what I had learned in college. Looking back, I just needed to have reviewed Unit 1 – intro and Unit 2 – derivatives. Calculus for ML – this amazing animated video explains calculus and backpropagation Information Theory – easy-to-understand book on information theory called Information Theory: A Tutorial Introduction. Statistics and Probability – the StatQuest YouTube channel Machine Learning Stanford Intro to Machine Learning by Andrew Ng – Stanford's CS229, the intro to machine learning course, published their lectures on YouTube for free. I watched lectures 1, 2, 3, 4, 8, 9, 11, 12, and 13, and I skipped the rest since I was eager to move onto deep learning. The course also offers a free set of course notes, which are very well written. Caltech Machine Learning – Caltech's machine learning lectures on YouTube, less mathematical and more intuition based Deep Learning Andrej Karpathy's Zero to Hero Series – Andrej Karpathy, an AI researcher who graduated with a Stanford PhD and led Tesla AI for several years, released an amazing series of hands on lectures on YouTube. highly highly recommend Neural networks – Stanford's CS231n course notes and lecture videos were my gateway drug, so to speak, into the world of deep learning. Transformers and LLMs Transformers – watched these two lectures: lecture from the University of Waterloo and lecture from the University of Michigan. I have also heard good things about Jay Alammar's The Illustrated Transformer guide ChatGPT Explainer – Wolfram's YouTube explainer video on ChatGPT Interactive LLM Visualization – This LLM visualization that you can play with in your browser is hands down the best interactive experience with an LLM. Financial Times' Transformer Explainer – The Financial Times released a lovely interactive article that explains the transformer very well. Residual Learning – 2023 Future Science Prize Laureates Lecture on residual learning. Efficient ML and GPUs How are Microchips Made? – This YouTube video by Branch Education is one of the best free educational videos on the internet, regardless of subject, but also, it's the best video on understanding microchips. CUDA – My FAANG coworkers acquired their CUDA knowledge from this series of lectures. TinyML and Efficient Deep Learning Computing – 2023 lectures on efficient ML techniques online. Chip War – Chip War is a bestselling book published in 2022 about microchip technology whose beginning chapters on the invention of the microchip actually explain CPUs very well
• SebFender 2y ago
  oh! 2/ recommendation is an absolute masterpiece of simplicity and effectiveness - cheers for that!
• srush 2y ago
  These slides from Lucas Beyer are pretty nice. https://docs.google.com/presentation/d/1ZXFIhYczos679r70Yu8vV9uO6B1J0ztzeDxbnBxD1S0/edit#slide=id.g13dd67c5ab8_0_54 https://docs.google.com/presentation/d/1ZXFIhYczos679r70Yu8v...