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        <description>&lt;https://www.thelmbook.com&gt;



This is the supporting wiki for the book The Hundred-Page Machine Learning Book by Andriy Burkov. The book is now available on Amazon and most major online bookstores.

The wiki contains pages that extend some book chapters with additional information: Q&amp;A, code snippets, further reading, tools, and other relevant resources.</description>
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        <description>[ NOTHING done overseas ]  TX based 
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        <description>Recommended Reading

	*  Overview of the Probably Approximately Correct (PAC) Framework by David Haussler
	*  Chapter 7 of Machine Learning by Tom Mitchell (1997)

Recommended Watching

	*  PAC Learning by Georgia Tech/Udacity (2015).</description>
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        <description>Image Generation

	*  GAN by Google
	*  Large Scale GAN Training for High Fidelity Natural Image Synthesis by Brock et al (2018)
	*  Image Transformer by Parmar et all (2018)
	*  The Illustrated Stable Diffusion by Jay Alammar
	*  NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis by Mildenhall et all (2020)
	*  Nerfies: Deformable Neural Radiance Fields by Park et al (2021)

Text Generation

	*  Training language models to follow instructions with human feedback by Ouyang et…</description>
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        <description>Recommended Reading with love

	*  Reinforcement Learning: An Introduction, Second Edition by Sutton and Barto (2018)...

Lectures

	*   Reinforcement Learning Course by Deep Mind and University College London (2018)
	*   Stanford CS234: Reinforcement Learning by Stanford University (2019)</description>
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