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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 次观看 • 5 个月前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

8 条评论

Eugene Smarts 的头像

Eugene Smarts5 个月前

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 Galloni 的头像

Stefano Galloni5 个月前

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

euno 的头像

euno5 个月前

14 minutes ago

Oxy_moron 的头像

Oxy_moron5 个月前

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

🎤Yogesh🎸 的头像

🎤Yogesh🎸5 个月前

Playlist

Havox 的头像

Havox5 个月前

Can I get this whole playlist anyone please ?

BearTheory 的头像

BearTheory5 个月前

Knowledge with perception

Adel Bucetta 的头像

Adel Bucetta5 个月前

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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