Deep Learning for Coders with Fastai and PyTorch

Name: Deep Learning for Coders with Fastai and PyTorch
Author: Jeremy Howard, Sylvain Gugger

Jeremy Howard, Sylvain Gugger

Deep learning has the reputation as an exclusive domain for math PhDs. Not so. With this book, programmers comfortable with Python will learn how to get started with deep learning right away.

10 score

#258 overall · #19 in Machine Learning

↓9

Score based on developer article recommendations — not sales data or reviews.

Machine Learning(41)Python(32)AI / ML(51) Intermediate Deep LearningMlops

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🟢 Developer Verdict

Empowers Python developers to quickly grasp and apply deep learning concepts using fastai and PyTorch, demystifying the field for practical application.

Read this if

✓ You want to learn deep learning from a coder's perspective, not a math-heavy one.
✓ You are comfortable with Python and want to use fastai and PyTorch.
✓ You aim to build practical deep learning applications quickly.

Skip this for now if

✗ You seek a deep dive into the underlying mathematical theories of AI.
✗ You prefer learning deep learning with TensorFlow or Keras primarily.
✗ You are an absolute beginner to programming or machine learning.

Developer signal: Overwhelming Consensus · 100% 4 analyzed mentions

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🔄 Compare & Reading Path

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Deep Learning with PyTorch Choose this for a more hands-on, practical approach Intermediate

💬 What Developers Say

"Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD"
— puratabla · Convert Tensorflow to Pytorch Model. in 2025? · Oct 12, 2025

"Deep Learning for Coders with Fastai and PyTorch: AI Applications Without a PhD"
— anna_golubkova · How to Prune Networks in Pytorch in 2025? · Oct 12, 2025