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课程目录# U* T4 x4 `1 _$ f v+ ?
CS231n Winter 2016 Lecture 1 Introduction and Historical Context.mp4
+ d2 x9 e9 ~1 iCS231n Winter 2016 Lecture 2 Data-driven approach kNN Linear Classification 1.mp4. T1 A+ G) G+ m# s, U J
CS231n Winter 2016 Lecture 3 Linear Classification 2 Optimization.mp4
8 o) _& Y7 C/ Q9 {6 S0 ECS231n Winter 2016 Lecture 4 Backpropagation Neural Networks 1.mp46 g" K) }$ g) X
CS231n Winter 2016 Lecture 5 Neural Networks Part 2.mp4
, `0 z; P( z' B# XCS231n Winter 2016 Lecture 6 Neural Networks Part 3 Intro to ConvNets.mp4
- @% x9 y. z% k b3 ^CS231n Winter 2016 Lecture 7 Convolutional Neural Networks.mp4 c) F, |% \8 d/ \3 |+ g! n& h4 `
CS231n Winter 2016 Lecture 8 Localization and Detection.mp47 _4 @* T8 F" P: M) [2 c$ s
CS231n Winter 2016 Lecture 9 Visualization Deep Dream Neural Style Adversarial Examples.mp40 T) r$ c5 w5 _$ Q5 K5 q0 I! M
CS231n Winter 2016 Lecture 10 Recurrent Neural Networks Image Captioning LSTM.mp4
7 }: b5 l) [5 m9 f* lCS231n Winter 2016 Lecture 11 ConvNets in practice.mp4# I) O( U$ I& H
CS231n Winter 2016 Lecture 12 Deep Learning libraries.mp4
1 s( p, P3 `$ C; x" G7 @CS231n Winter 2016 Lecture 13 Segmentation soft attention spatial transformers.mp4: m) ~! J. i8 N( u6 y
CS231n Winter 2016 Lecture 14 Videos and Unsupervised Learning.mp4 y; K5 z" U' E# n2 m/ _8 j
CS231n Winter 2016 Lecture 15 Invited Talk by Jeff Dean.mp4
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