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@_rohit_tiwari_: This 185-page book unlocks the secrets of deep learning. https://drive.google.com/file/d/188pV6Fn0mgzY1UYMsYrHK_q5znjW8…

X AI KOLs Timeline · 2026-06-09 Cached

A Twitter user shares a 185-page deep learning book covering foundations, deep models, architectures, applications, and compute schism topics via a Google Drive link.

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@techyoutbe: Phase 00: Setup & Tooling (12 lessons) Phase 01: Math Foundations (22 lessons) Phase 02: ML Fundamentals (18 lessons) P…

X AI KOLs Timeline · 2026-06-04 Cached

A structured 19-phase AI/ML learning curriculum covering topics from setup and math to capstone projects, created by @ghumare64.

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@yacinelearning: very awesome resource from hugging face with available slides about how they generated 1T synthetic data a really cool …

X AI KOLs Following · 2026-05-26 Cached

Hugging Face shared slides detailing how they generated 1 trillion tokens of synthetic data for training foundation models.

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@KanikaBK: MIT JUST MADE THEIR DEEP LEARNING BIBLE COMPLETELY FREE. No paywall or signup. The full book is available right now. Th…

X AI KOLs Timeline · 2026-05-24 Cached

MIT has made the entire 'Deep Learning' textbook by Goodfellow, Bengio, and Courville freely available online without paywall or signup, providing over 800 pages of foundational knowledge.

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@_vmlops: Artificial Intelligence & Machine Learning Explained by Stanford https://drive.google.com/file/d/1H2_QWjauxlrj1UKO2nPd8…

X AI KOLs Timeline · 2026-05-21

Stanford provides an explanatory document on Artificial Intelligence & Machine Learning, available via Google Drive.

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@wsl8297: There is a repository on GitHub that clearly organizes the research lineage of Speech Language Models (SpeechLM): Awesome-SpeechLM-Survey. It comprehensively organizes classification frameworks, representative models, training datasets, and evaluation benchmarks into a single 'knowledge map,' making it time-efficient to look up materials, fill in background knowledge, and find benchmarks.

X AI KOLs Timeline · 2026-05-14 Cached

The Awesome-SpeechLM-Survey repository on GitHub systematically organizes the research lineage of speech language models, including classification frameworks, representative models, training datasets, and evaluation benchmarks. It serves as a knowledge map for understanding the field.

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@FinanceYF5: Attention, Distribution, Influence, Taste—This is how future media is built. Ollie Forsyth releases the ultimate creator map, covering all new media creators in the tech field:

X AI KOLs Following · 2026-05-08 Cached

Ollie Forsyth released an ultimate creator map covering new media creators in the tech field, emphasizing the importance of attention, distribution, influence, and taste in building future media.

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