Deep Learning
refer to "Deep Learning Tutorial" by Yann LeCun and others
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461399/pasted-from-clipboard.png)
Deep Learning
Wikipedia says:
“Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using multiple processing layers, with complex structures or otherwise, composed of multiple non-linear transformations.”
Machine Learning
Text
SCALE UP
Totally NEW?
Neural Nets
Perception
RNN
CNN
RBM
DBN
D-AE
AlexNet
GoogLeNet
McCulloch&Pitt 1943
Rosenblatt 1958
Grossberg 1973
Fufushima 1979
Hinton 1999
Hinton 2006
Vincent 2008
Alex 2012
Szegedy 2015
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461767/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461768/pasted-from-clipboard.png)
Really need DEEP?
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461440/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461442/pasted-from-clipboard.png)
What is Approach?
multi layers...
but...each layer has
complex model
with small data
The researchers say even they weren’t sure this new approach (152 layers!) was going to be successful – until it was.
“We even didn’t believe this single idea could be so significant,”
said Jian Sun, a principal research manager at Microsoft Research
is DL Omnipotent?
Applications
Scene Recognition (CNN)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461450/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461499/pasted-from-clipboard.png)
Visual Style Recognition (CNN)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461451/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461497/pasted-from-clipboard.png)
Object Detection (R-CNN)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461455/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461495/pasted-from-clipboard.png)
Image Captioning (CNN+LSTM)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461460/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461492/pasted-from-clipboard.png)
Segmentation (DeconvNet)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461462/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461491/pasted-from-clipboard.png)
Deep Visuomotor Control
(CNN)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461473/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461489/pasted-from-clipboard.png)
Neural Style (CNN)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461481/pasted-from-clipboard.png)
Text
Text
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461487/pasted-from-clipboard.png)
Deep Learning Trends
- Multi-modal(Image+Voice) -> 1 Label
- DL Best Practice -> Theory
Deep Learning Tools
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461347/pasted-from-clipboard.png)
Refer to
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461353/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461381/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461386/pasted-from-clipboard.png)
TensorFlow
Refer to "https://www.udacity.com/course/deep-learning--ud730"
How many Dimension need?
for Basic Image Processing
X = [B, W, H, C]
Basic Logistic Regression
a example of Machine Learning
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461692/pasted-from-clipboard.png)
AlexNet
a example of Deep Learning
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461735/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461739/pasted-from-clipboard.png)
GoogLeNet
a example of Deep Learning
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2461723/pasted-from-clipboard.png)
Image Recognition Demo
Prerequisite
- Python
- Development Environment
- Numpy
- Image Handling
- TensorFlow
- Training & Testing Data Prepartion
- General Machine Learning Methodology
- Deep Learning Practice
Python Scientific Ecosystem
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2692647/pasted-from-clipboard.png)
Python Ecosystem
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2692630/pasted-from-clipboard.png)
Development Environment
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2692533/pasted-from-clipboard.png)
Development Environment
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2692544/pasted-from-clipboard.png)
NumPy = N-Dim Array
- Python List
- 여러가지 타입의 원소
- 메모리 용량이 크고 속도가 느림
- nesting 가능
- 전체 연산 불가
- NumPy Array
- 동일 타입의 원소
- 메모리 최적화, 계산 속도 향상
- 크기(dimension)이 명확하게 정의
- 전체 연산 가능
Live Coding Practice
- Image Handling
- Training & Testing Data Prepartion
- General Machine Learning Practice
- Deep Learning Practice
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2693086/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2693109/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2693094/pasted-from-clipboard.png)
![](https://s3.amazonaws.com/media-p.slid.es/uploads/356717/images/2693101/pasted-from-clipboard.png)
TensorFlow Development
By SURK PARK
TensorFlow Development
- 898