Learning

Stanford CS229: Machine Learning - Linear Regression and Gradient Descent | Lecture 2 (Autumn 2018)
01:18:17
Stanford CS229: Machine Learning | Summer 2019 | Lecture 20 - Variational Autoencoder
01:52:36
AI in Radiology at Stanford: Rise of the Machines
00:15:55
Lecture 11 | Detection and Segmentation
01:14:26
Lecture 14 | Deep Reinforcement Learning
01:04:01
Stanford CS229: Machine Learning | Summer 2019 | Lecture 1 - Introduction and Linear Algebra
01:51:13
Stanford CS330: Deep Multi-task & Meta Learning I 2021 I Lecture 2
01:18:47
Stanford CS224N: NLP with Deep Learning | Winter 2019 | Lecture 6 – Language Models and RNNs
01:08:25
Andrew Ng’s Machine Learning Specialization 2022 | What is it and is it worth taking
00:12:07
Lecture 9 | CNN Architectures
01:17:40

Lecture 9 | CNN Architectures
Generative AI
2,631,110 Views · 4 years ago

Machine Learning 2 - Features, Neural Networks | Stanford CS221: AI (Autumn 2019)
01:22:23
Lecture 7 | Training Neural Networks II
01:15:30
Symbols and Rules with Deep Learning - Ellie Pavlick | Stanford MLSys #54
01:01:40
Lecture 10 | Recurrent Neural Networks
01:13:09
Stanford Seminar -
01:17:46

Stanford Seminar -
Generative AI
2,401,394 Views · 4 years ago

Stanford CS224N NLP with Deep Learning | Winter 2021 | Lecture 7 - Translation, Seq2Seq, Attention
01:18:55


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