coscup nas也可以揀土豆
TRANSCRIPT
COSCUP
NAS也可以揀土豆Johnson & Evans
Agenda
1. NAS也可以揀土豆
2. CNN (卷積神經網絡)
3. Open Source Tool: Tensorflow
4. Demo
這是土豆
需求:攝影師分類照片
Agenda
1. NAS也可以揀土豆
2. CNN (卷積神經網絡)
3. Open Source Tool: Tensorflow
4. Demo
2012 ImageNet
Classifiy 1000 class image
CNN: Convolution Neural Network (卷積神經網絡)
Visualization: http://scs.ryerson.ca/~aharley/vis/conv/
Machine Learning 一線曙光
feature representation by human => by machine
Agenda
1. NAS也可以揀土豆
2. CNN (卷積神經網絡)
3. Open Source Tool: Tensorflow
4. Demo
Open Source Tool
Tensorflow (Google Open Source Lib for ML)
Google從2012年初開始在內部專案中使用機器學習技術,
2014年擁抱機器學習的專案量更快速成長,至今超過1,500
個內部專案採用,除了 AlphaGo以外,還有地圖服務、相片
服務、Gmail、語音辨識、Android、YouTube、翻譯、機器
人研究、自然語言研究、醫藥研發等專案。2016-04
http://www.ithome.com.tw/news/105099 https://en.wikipedia.org/wiki/TensorFlow
Google Inception CNN Model (2014 ImageNet) (開源)
https://github.com/tensorflow/models/tree/master/inception
7,699 USD
GPU: GK110B
Core: 2880
1000 class 138,357,544 paramshttp://www.slideshare.net/cagechung/nas-65206227?ref=http://kaichu.io/2016/08/22/retrain-inception-model-for-nas/
BIG TIME
BIG DATA
BIG MONEY
BIG MODEL
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
前面保留,只重新訓練最後一層
10min + (one time preprocessing: 40min)
R380x1
539 images (100/class)
Much faster
Cheaper
(E5-2620 * 1, 32G RAM, NO GPU)
Relatively small
Agenda
1. NAS也可以揀土豆
2. CNN (卷積神經網絡)
3. Open Source Tool: Tensorflow
4. Demo
Getcha Pikachu
x 118
x 114
90.8%
那可否分電擊獸、雷精靈、閃電鳥
ClassAccuracy
(80/10/10)
Training
Time
Prediction
Time
2 90.8% 10m13.457s3s (mba)
1s (mbp)
4 87.0% 10m10.662s
4 94.0% 11m56.550s
7 85.4% 14m32.250s
Demo
ArkEase Pro 2.6.4.0216 (10.20.101.138)
HW: R380
Conclusion & Future Work
機器學習離我們不遠
=> 攝影師/使用者自己訓練照片分類(Small Data => Big Model)
Realtime stream prediction
Add user feedback to improve model
151 Pokemon Model?
臭泥, 臭臭泥與百變怪?
ArkEase Pro 可以抓(偵測)寶可夢NAS可以揀土豆
Special Thanks
Bill 幫忙安裝 ArkEasePro R380
ArkEase Pro team 提供2.6環境, Carlcarl test docker environment, Albert R380 info
KW 提供有趣點子