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Neural networks explained from first principles: how simple linear pieces combine into richer models, and why layered representations make machine learning more powerful. MIT OpenCourseWare, 6.036 Introduction to Machine Learning, Fall 2020.

tetsuo

239,717 subscribers

11,055 views • 5 months ago •via X (Twitter)

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8 Comments

Eugene Smarts5 months ago

understanding the fundamentals is crucial, but implementation can be tricky. diving into real-world applications will reveal the trade-offs in complexity versus performance.

Stefano Galloni5 months ago

AI is what happens when math doesn't give up.😛

euno5 months ago

14 minutes ago

Oxy_moron5 months ago

This is nice and I love the simplification of all of them. It makes it easier to understand

🎤Yogesh🎸5 months ago

Playlist

Havox5 months ago

Can I get this whole playlist anyone please ?

BearTheory5 months ago

Knowledge with perception

Adel Bucetta5 months ago

the real unlock is combining these simpler components in a way that lets them learn from each other, creating complex behaviors without needing massive datasets

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