Whether we like it or not, deep learning is eating the world. Several weeks ago, I decided to learn how it works. It’s the Wild West out here. Everyone recommends different resources and makes different assumptions about how much time you have.
I looked at a bunch and removed some guesswork on both fronts: These resources are simply the best, better than all the rest, and maybe more importantly, they give you reliable options whether you want your journey to be 60 minutes or 6 years.
I’ve included some details on prerequisites at the end. Regardless of background, everyone should check out the first link. 3Blue1Brown is a legend.
1. Hour
- Neural networks playlist, 3Blue1Brown
- Deep Learning with PyTorch: A 60 Minute Blitz, Soumith Chintala (PyTorch documentation)
2. Day
- Learn PyTorch for deep learning in a day, Daniel Bourke
- I tried to learn as much deep learning math as I could in 24 hours, Phosphorus (Less Wrong blog)
3. Season
- Books
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Deep Learning, Ian Goodfellow, Yoshua Bengio, and Aaron Courville
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Deep Learning with Python, François Chollet
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Neural Networks and Deep Learning, Michael Nielsen
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Machine Learning with PyTorch and Scikit-Learn, Sebastian Raschka
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- Courses
- course.fast.ai, Jeremy Howard
- deeplearning.ai, Andrew Ng & others
- Elements of AI, University of Helsinki
- Dive Into Deep Learning, Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola
- Neural Networks: Zero to Hero, Andrej Karpathy
- Learn Machine Learning in 3 Months, Siraj Raval
4. Decade
- Go to grad school
- Roadmaps
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Machine Learning Roadmap, Daniel Bourke
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Complete Roadmap to be a Deep Learning Engineer, Let the Data Confess
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- Resource lists
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Awesome Deep Learning, ChristosChristofidis
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Crème de la crème of AI courses, SkalskiP
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Deep Learning.md, brylevkirill
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- Miscellaneous
- Papers With Code, Meta AI Research
- Two Minute Papers (Youtube Channel), Károly Zsolnai-Fehér
- Sentdex (Youtube Channel), Harrison Kinsley
A Note on Prerequisites
It’s a free country. Learn what you want along the way. All the resources above are fairly clear about what’s needed.
That said, if you want to embark on a serious course of study, here are a few central building blocks they all share that you’ll need to be comfortable with.
- Manipulating vectors and matrices
- Finding derivatives
- Gradient descent
- Basic Python programming
It’ll also help to know:
- How to learn
- How to prompt tools like ChatGPT effectively, for broad explanations.
- How other kinds of advanced machine learning besides deep learning work, if you want to become a domain expert one day.
Happy learning 💡