Deep Learning from Scratch
by Seth Weidman · first published 2019
12mentions
4recommended by
9HN commenters
2019–2024first – last mentioned
44% recommend44% neutral11% critical
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I am/was in this scenario. I'm sure there are other resources out there specifically aimed at developers, but a book I'm reading now is "Deep Learning From Scratch" by Seth Weidman. He takes a different approach, by explaining concepts in three distinct methods: a mathematical way, by using diagrams and by showing the code. I like this approach because it allows…
on “Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory” ↗If you want just one book to learn all things deep learning from scratch with coding including the latest techniques, it should be Dive into deep learning [0]. Really underrated and not well-known. [0] https://d2l.ai/
on “Intro to Deep Learning” ↗1. Nature of Code- simulating and modeling many things in nature. 2. Data Science from Scratch- building a Data Science library from scratch. 3. Deep Learning from Scratch- building a Deep Learning library from scratch. 4. Realm of Racket and 5. Land of Lisp- developing games with Racket and Lisp. 6. The Little Schemer- not only teaches you to think recursively, but also…
on “Ask HN: Books like “Crafting interpreters” or “The ray tracer challenge”?” ↗I think all serious researchers have implemented core Deep Learning algorithms from scratch. I know I have. There are two books that do exactly this: 1. Deep Learning from Scratch 2. Data Science from Scratch In these books, you implement each part of the DL pipeline, from scratch, in Python. There is also a GitHub project call Minitorch that teaches you the innet workings of…
on “The Little Learner: A Straight Line to Deep Learning” ↗The handouts at https://fleuret.org/dlc/ are fantastic. Also two books: Data Science from Scratch and Deep Learning from Scratch. They are more hand-on, but you'll build all the low-level things in Python and learn a lot.
on “Ask HN: Resources to brush up from 'Intro to ML' to current LLMs/generative AI?” ↗There is also the book Deep Learning from Scratch.
on “Minitorch: Implement the Torch API from Scratch, from Cornell Tech” ↗…focused on teaching how to develop a Deep Learning library, and not teaching Deep Learning through implementing things from scratch. If that's what you want, then there are: - Data Science from Scratch - Deep Learning from Scratch
on “Minitorch: Implement the Torch API from Scratch, from Cornell Tech” ↗…first 10 of 60 steps, and the link to purchase (https://www.amazon.co.jp/dp/4873119065/ref=cm_sw_em_r_mt_dp_...) is for the Japanese version. There's another github link (https://github.com/oreilly-japan/deep-learning-from-scratch-...) with the code for all 60 steps, but not the explanatory text.
on “Show HN: Deep Learning Framework from scratch (60 step tutorial)” ↗I recently published a series of 16 blog posts Deep Learning from Scratch to GPU that does exactly that! [0] I also started working on a book titled "Deep Learning for Programmers"[1] that takes it even further! You can subscribe today and start reading the drafts as they…
on “Practical Deep Learning for Coders” ↗Dragan, thank you for your continued hard work (and your well written posts!) I haven’t got the time yet, but I’m very much looking forward to reading both your series of “deep learning from scratch” posts and your books.
on “Fast Tensors in Clojure – A Sneak Peek” ↗what about Data Science from Scratch, Deep Learning from Scratch, and similar books where they just use numpy or something and do everything from mostly first principles?
on “Ask HN: Tutorials written with heavy dependencies” ↗The last commit in the repo of "Deep Learning from Scratch" was 5 years ago. It is hopelessly outdated. The field is changing very fast.
on “Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory” ↗