不定时的看看深度学习deep learning

11/2 stanford DL tutorial section 1

11/3 stanford DL tutorial, multi-layer NN, CNN
unsupervised learning: autoencoders, PCA/whitening
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TODO: remainder of unsupervised learning and self-taught learning
exercise on CNN
then on with 231n.

11/7
tSNE
online learning https://www.coursera.org/learn/ml-classification/lecture/vEF6f/timeline-of-scalable-machine-learning-stochastic-gradient
231n - visualize CNN/RNN intro
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TODO:
stanford tutorial: remainder of unsupervised learning and self-taught learning
exercise on CNN

came across an interesting playlist on youtube:
2 min papers:
https://www.youtube.com/user/keeroyz/playlists
quite fun
kinda like "talking machines" podcast (sadly, it seems to be no longer actively updating)
also found some other podcasts on software engineering or ML, but they weren't as good as talking machines

谢谢K姐分享！

finished video part of cs231n. now on to toy examples and finding some real use cases from work, maybe
recently started a refresher using the udacity legacy course intro to AI. since my experience in ML/DL etc is completely self taught, this course filled some gaps in the knowledge landscape.

谢谢K姐分享这么多好东西
可惜我基础太差，根本没能力看这些。先存下来当胡萝卜挂着吧。

Docker image
最好的宝贝，没有之一 https://github.com/saiprashanths/dl-docker 好用的想哭。不然就会抓狂到想哭。
caffe model zoo:
https://github.com/BVLC/caffe/wiki/Model-Zoo
有人说可以用这个https://github.com/ethereon/caffe-tensorflow 把其变成TF zoo Deep Viz toolbox
https://github.com/yosinski/deep-visualization-toolbox

谢谢分享！好多东东！

谢谢分享！收藏学习！