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Core readings

by @stats385 · last added 2026-09-24 · 7 items [core]

Shelf starters: textbooks, the Nature overview, and statistical perspectives every student should know.

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* Emergence of Simple-cell Receptive Field Properties
Sparse coding / V1 inspiration paper (Olshausen & Field) — Lecture 1 background reading.
courses.cs.washington.edu · node›
* ACM Turing Award lectures (Hinton, LeCun, …)
Video lectures by Turing awardees — pair with the Nature article for a narrative arc.
amturing.acm.org · node›
* History and Development of Neural Networks
Historical survey of neural nets — useful context before modern architecture papers.
sciencedirect.com · node›
* An Overview from the Statistical Perspective
Course-listed statistical overview of deep learning — bridges ML practice and stats language.
arxiv.org · node›
* Dive into Deep Learning (d2l.ai)
Interactive tutorials with code — excellent companion when you need implementations alongside theory.
d2l.ai · node›
* Deep Learning — LeCun, Bengio & Hinton (Nature 2015)
The three Turing awardees’ Nature overview — best short intro to why deep learning worked.
nature.com · node›
* Deep Learning Book (Goodfellow, Bengio, Courville)
Canonical textbook. Use as background reference; skim architecture & optimization chapters early.
deeplearningbook.org · node›
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