Deep Learning for Coders with fastai and PyTorch
AI Applications Without a PhD
by Jeremy Howard
Should I read this?
Recommended by 1 source and appears in Pytorch, Deep Learning, and Machine Learning.
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this handson guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How With fastai, the first library to provide a consistent inte...
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Why recommended
Recommended by 1 source and appears in Pytorch, Deep Learning, and Machine Learning.
Recommended by notable people
People and public figures who have recommended this book.
Recommendation Signals
Recommendation proof is sourced from public posts, interviews, reading lists, and cited references.
Miguel de Icaza
“I love the new book not only it teaches you AI in a quite novel way, the paper it is printed on is glorious and printed in full color. Just like “cooking for geeks” changed my life, this one did too. This is a book worth owning in paper:”
Appears In
Not sure if this is the right fit?
Consider Life 3.0 by Max Tegmark. Recommended by 18 sources.
“Life 3.0 reads like a long, wide-ranging conversation with a physicist who loves big if-then thought experiments. The useful part is its panoramic sweep across possible AI futures—from job automation to cosmic colonization—forcing you to consider timelines you might otherwise avoid. The limitation is that the speculative breadth often outruns the depth; chapters can feel meandering, and some readers will find the cosmic-scale scenarios too detached from practical concerns, making it hard to ground in real urgency.”
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Each recommendation is collected from a public source — interviews, articles, or curated lists — and linked to its original URL. Books with many verifiable recommendations from respected people rank higher.
Deep Learning for Coders with fastai and PyTorch
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