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A curated collection of machine learning resources
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readme.md

readme.md

This repository is in early development - a refactor of my machine learning resources. If you like this check out my reinforcement learning course and rl-resources repos.

If you are starting out with machine learning

For neural networks - Deep Learning - Ian Goodfellow, Yoshua Bengio and Aaron Courville

For everything else (linear models, random forests etc)

Podcasts

Lex Fridman - AI Podcast

The Bitter Lesson - Rich Sutton - 2019

One thing that should be learned from the bitter lesson is the great power of general purpose methods, of methods that continue to scale with increased computation even as the available computation becomes very great. The two methods that seem to scale arbitrarily in this way are search and learning.

The second general point to be learned from the bitter lesson is that the actual contents of minds are tremendously, irredeemably complex; we should stop trying to find simple ways to think about the contents of minds, such as simple ways to think about space, objects, multiple agents, or symmetries.

Talks

Demis Hassabis (CEO DeepMind) – Artificial Intelligence and the Future

Artificial Intelligence is the New Electricity - Andrew Ng

Nuts and Bolts of Applying Deep Learning - Andrew Ng

Blog posts

Software 2.0 - Andrej Karpathy (Tesla & OpenAI)

Non-technical overviews

The basics of modern AI—how does it work and will it destroy society this year? - Ars Technica

Dairy farming, solar panels, and diagnosing Parkinson's disease: what can you do with deep learning? - fast.ai

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World - Pedro Domingos

Criticism

2018 - Artificial intelligence: winter is coming

2019 - Our Entire AI Revolution Is Built On A Correlation House Of Cards

What worries me about AI – François Chollet

Domain specific

The financial world wants to open AI's boxes – MIT Technology Review

Misc

Paperclip maximizer

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