Learn deep learning/Browse recommendations

Browse all recommendations

Learn deep learning. 7 people, 13 books. Recommendation records: 14.

Every matching recommendation record appears here, grouped by person and book. Editorial starting points are on the collection overview.

Page 1 of 1 · Recommendation records on this page: 14.

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Cover unavailable for Deep Learning

Deep Learning

Portrait unavailable for Andrej KarpathyAndrej Karpathy

Suggested as more advanced technical reading.

Recommended · Wording not verified Source: Andrej Karpathy
Evidence details What a Deep Neural Network thinks about your #selfie

The concluding learning-resources passage directs advanced readers to the book then being written. This 2015 guidance predates the final 2016 edition; it does not claim he endorsed a later revision or every book claim.

This text documents what the source says, but it is not verified as a word-for-word quote.

Andrej Karpathy · 2015-10-25 · accessed 2026-10-02

Article · Original written source

The concluding learning-resources passage directs advanced readers to the book then being written. This 2015 guidance predates the final 2016 edition; it does not claim he endorsed a later revision or every book claim.

View evidence on Andrej Karpathy’s profile

Cover unavailable for Deep Learning

Deep Learning

Portrait unavailable for Sebastian RaschkaSebastian Raschka

Explicitly recommends the upcoming Deep Learning manuscript after ML/statistical foundations.

Recommended · Wording not verified Source: Sebastian Raschka
Evidence details How would your curriculum for a machine learning beginner look like?

Existing catalog work. Recommendation predates 2016 publication; do not assert later-edition endorsement.

This text documents what the source says, but it is not verified as a word-for-word quote.

Sebastian Raschka · undated · accessed 2026-10-05

Article · Historical personal study-plan recommendations

Explicitly recommends the upcoming Deep Learning manuscript after ML/statistical foundations.

View evidence on Sebastian Raschka’s profile

Cover unavailable for Neural Networks and Deep Learning

Neural Networks and Deep Learning

Portrait unavailable for Andrej KarpathyAndrej Karpathy

Suggested as a starting resource for beginners learning neural networks.

Recommended · Wording not verified Source: Andrej Karpathy
Evidence details What a Deep Neural Network thinks about your #selfie

In the conclusion of his 2015 article, Karpathy points beginners to Michael Nielsen’s tutorials. This is historical guidance about that work, not an endorsement of every later revision or a modern software setup.

This text documents what the source says, but it is not verified as a word-for-word quote.

Andrej Karpathy · 2015-10-25 · accessed 2026-10-05

Article · Original written source

The conclusion directs beginners to Michael Nielsen’s tutorials and links neuralnetworksanddeeplearning.com. Nielsen’s own companion repository identifies the linked work as his book Neural Networks and Deep Learning. Recommendation wording here is a paraphrase, not a direct quote.

View evidence on Andrej Karpathy’s profile

Cover unavailable for Deep Learning with PyTorch

Deep Learning with PyTorch

Portrait unavailable for Sebastian RaschkaSebastian Raschka

Original independent review says beginners may start with this book and experts may find chapter3 worthwhile; positive reader-facing verdict, without payment/review copy.

Recommended · Wording not verified Source: Sebastian Raschka
Evidence details Deep Learning with PyTorch book review

2020 book strongly computer vision focused, no transformers/LLMs; requires Python; source says introductory for experienced practitioners.

This text documents what the source says, but it is not verified as a word-for-word quote.

Sebastian Raschka · 2021-01-21 · accessed 2026-10-05

Article · Personal book review

Original independent review says beginners may start with this book and experts may find chapter3 worthwhile; positive reader-facing verdict, without payment/review copy.

View evidence on Sebastian Raschka’s profile

Cover unavailable for Interpretable Machine Learning

Interpretable Machine Learning

Portrait unavailable for Sebastian RaschkaSebastian Raschka
I recommend reading the book itself if you want to learn about machine learning and interpretability.
Recommended · Exact quote Source: Sebastian Raschka
Evidence details Interpretable Machine Learning book review

Historical 2020 print and then-current online book; source notes evolving contents. Do not describe current online edition as the endorsed edition.

The quote is taken word for word from the source.

Sebastian Raschka · 2020-08-26 · accessed 2026-10-05

Article · Personal book review

Original independent review explicitly recommends the book; declares no author affiliation or review copy.

View evidence on Sebastian Raschka’s profile

Cover unavailable for Introduction to Data Mining

Introduction to Data Mining

Portrait unavailable for Sebastian RaschkaSebastian Raschka
I can highly recommend the following book written by one of my former professors:
Recommended · Exact quote Source: Sebastian Raschka
Evidence details How would your curriculum for a machine learning beginner look like?

Historical pre-2016 advice; source explicitly identifies first edition. Do not imply recommendation of later edition with additional coauthor.

The quote is taken word for word from the source.

Sebastian Raschka · undated · accessed 2026-10-05

Article · Historical personal study-plan recommendations

Original personal beginner curriculum explicitly recommends the following item, Introduction to Data Mining (First Edition, 2005).

View evidence on Sebastian Raschka’s profile

Cover unavailable for Pattern Classification

Pattern Classification

Portrait unavailable for Sebastian RaschkaSebastian Raschka

Raschka suggests deepening statistical learning knowledge using one of three named books in a personal reading/study plan. This is an explicit reading-list context, not mere course bibliography.

Recommended · Wording not verified Source: Sebastian Raschka
Evidence details How would your curriculum for a machine learning beginner look like?

Historical study-plan recommendation. The source citation lists 2012; the publisher dates the second edition to 2000. No edition/year is asserted for this work-level catalog record.

This text documents what the source says, but it is not verified as a word-for-word quote.

Sebastian Raschka · undated · accessed 2026-10-05

Article · Historical personal study-plan recommendations

Raschka suggests deepening statistical learning knowledge using one of three named books in a personal reading/study plan. This is an explicit reading-list context, not mere course bibliography.

View evidence on Sebastian Raschka’s profile

Cover unavailable for Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning

Portrait unavailable for Sebastian RaschkaSebastian Raschka

Raschka suggests deepening statistical learning knowledge using one of three named books in a personal reading/study plan. This is an explicit reading-list context, not mere course bibliography.

Recommended · Wording not verified Source: Sebastian Raschka
Evidence details How would your curriculum for a machine learning beginner look like?

Undated historical pre-2016 study plan; publisher verifies first edition2006, sole author Christopher M. Bishop.

This text documents what the source says, but it is not verified as a word-for-word quote.

Sebastian Raschka · undated · accessed 2026-10-05

Article · Historical personal study-plan recommendations

Raschka suggests deepening statistical learning knowledge using one of three named books in a personal reading/study plan. This is an explicit reading-list context, not mere course bibliography.

View evidence on Sebastian Raschka’s profile

Cover unavailable for The Elements of Statistical Learning

The Elements of Statistical Learning

Portrait unavailable for Sebastian RaschkaSebastian Raschka

Raschka suggests deepening statistical learning knowledge using one of three named books in a personal reading/study plan. This is an explicit reading-list context, not mere course bibliography.

Recommended · Wording not verified Source: Sebastian Raschka
Evidence details How would your curriculum for a machine learning beginner look like?

Historical personal study plan. Publisher confirms Hastie/Tibshirani/Friedman secondedition2009; no newer edition asserted.

This text documents what the source says, but it is not verified as a word-for-word quote.

Sebastian Raschka · undated · accessed 2026-10-05

Article · Historical personal study-plan recommendations

Raschka suggests deepening statistical learning knowledge using one of three named books in a personal reading/study plan. This is an explicit reading-list context, not mere course bibliography.

View evidence on Sebastian Raschka’s profile

Cover unavailable for Build a Large Language Model (From Scratch)

Build a Large Language Model (From Scratch)

Portrait unavailable for Chip HuyenChip Huyen
This is the guide you need!
Recommended · Exact quote Source: Manning
Evidence details Build a Large Language Model (From Scratch)

Publisher-hosted attributed endorsement with explicit reader-facing instruction; the endorsement date is not given. Huyen is the recommender; Raschka is the author.

The quote is taken word for word from the source.

Manning · undated publisher endorsement · accessed 2026-10-05

Article · Publisher-hosted attributed endorsement

Manning attributes reader-facing guidance to Chip Huyen in its endorsements for this 2024 book.

View evidence on Chip Huyen’s profile

Cover unavailable for Dive into Deep Learning

Dive into Deep Learning

Jensen Huang in 2025Jensen Huang

The official book README attributes to Jensen Huang a reader-facing endorsement saying the book deserves attention from anyone wanting to understand deep learning.

Recommended · Wording not verified Source: Dive into Deep Learning authors
Evidence details Dive into Deep Learning: official README endorsements

Author-hosted promotional endorsement with reader-facing guidance, accepted by independent preliminary source review. This does not make Huang an AI researcher or imply endorsement of every later online revision.

This text documents what the source says, but it is not verified as a word-for-word quote.

Dive into Deep Learning authors · undated author-hosted endorsement · accessed 2026-10-05

Article · Author-hosted attributed endorsement

The official book README attributes to Jensen Huang a reader-facing endorsement saying the book deserves attention from anyone wanting to understand deep learning.

View evidence on Jensen Huang’s profile

Cover unavailable for Mathematics for Machine Learning

Mathematics for Machine Learning

Portrait unavailable for Pieter AbbeelPieter Abbeel
Highly recommended for anyone wanting a one-stop shop to acquire a deep understanding of machine learning foundations.
Evidence details Mathematics for Machine Learning

Author-hosted endorsement, undated, April2020 book; do not imply endorsement of every updated PDF.

The quote is taken word for word from the source.

Mathematics for Machine Learning authors · undated · accessed 2026-10-05

Article · Author-hosted attributed endorsement

Official authors companion site Testimonies attributes explicit reader recommendation to Pieter Abbeel.

View evidence on Pieter Abbeel’s profile

Cover unavailable for Probabilistic Machine Learning: Advanced Topics

Probabilistic Machine Learning: Advanced Topics

Portrait unavailable for Yoshua BengioYoshua Bengio
I therefore recommend it highly to all of them.
Recommended · Exact quote Source: Kevin P. Murphy
Evidence details Probabilistic Machine Learning: Advanced Topics

Author-hosted endorsement, undated, 2023 work; not a personal reading-list interview. Avoid endorsement of newer online revisions.

The quote is taken word for word from the source.

Kevin P. Murphy · undated · accessed 2026-10-05

Article · Author-hosted attributed endorsement

Attributed original endorsement explicitly recommends sequel to graduate CS students.

View evidence on Yoshua Bengio’s profile

Cover unavailable for The Little Book of Deep Learning

The Little Book of Deep Learning

Portrait unavailable for John CarmackJohn Carmack

Carmack praises this short book as a useful bridge from a vague understanding of neural networks to technical practice.

Recommended · Wording not verified Source: John Carmack
Evidence details John Carmack on The Little Book of Deep Learning

Favorable reader-facing technical guidance in his own public post. The current author-hosted update is not asserted as his endorsed edition.

This text documents what the source says, but it is not verified as a word-for-word quote.

John Carmack · 2023-12-13 · accessed 2026-10-01

Social post · Own public reading recommendation

Carmack’s post links to the author’s free-book page: https://fleuret.org/francois/lbdl.html. The author warns about unauthorized commercial copies. Later updates are not asserted as Carmack’s endorsed edition.

View evidence on John Carmack’s profile

End of recommendations in this collection.