The document provides an overview of deep learning, including its history from the perceptron to the revival with backpropagation in the 1980s. It describes the explosion of deep learning with seminal papers in 2006, availability of large labeled datasets, powerful computing hardware, and open source software. Popular deep learning models like convolutional neural networks and recurrent neural networks are explained. Applications of deep learning like image segmentation, self-driving cars, asset management, and recommendation engines are also mentioned.

1. Deep Learning:
Fundamentals and Practice
Rohan Wickramasuriya

2. Deep Learning
Is it real?
Image Sources:
https://www.popularmechanics.com/cars/car-technology/a19737872/self-driving-autonomous-cars-talk-debate/
https://www.kdnuggets.com/wp-content/uploads/computer-deep-learning-algorithm-painting-masters-fb__700.jpg

4. History of Deep Learning
Perceptron and the AI Winter
Output

5. History of Deep Learning
Backpropagation: The Revival of AI
W = W – LR* ∂E/∂W

6. History of Deep Learning
Deep Learning Explosion
G. Hinton’s seminal paper in 2006
Large labelled datasets
Powerful Computing Hardware
Open source software
Breakthrough Ideas

7. Popular Deep Learning Models
Convolutional
Neural
Networks
Recurrent
Neural
Networks
Generative
Models (e.g.
GAN)

8. Convolutional Neural Network (CNN)
Image Sources:
https://medium.com/@Aj.Cheng/convolutional-neural-network-d9f69e473feb

9. CNN
Main Steps
Convolution
Non-linear activation
Pooling
Classification

10. CNN
Convolution
Image Sources:
https://medium.com/@Aj.Cheng/convolutional-neural-network-d9f69e473feb

11. CNN
Convolution
Image Sources:
https://medium.com/@Aj.Cheng/convolutional-neural-network-d9f69e473feb

12. CNN
Non Linear Activation
Image Sources:
https://medium.com/@Aj.Cheng/convolutional-neural-network-d9f69e473feb

13. CNN
Max Pooling
Image Sources:
https://medium.com/@Aj.Cheng/convolutional-neural-network-d9f69e473feb

14. CNN
Story so far & Fully Connected Layers
Image Sources:
https://adeshpande3.github.io/A-Beginner%27s-Guide-To-Understanding-Convolutional-Neural-Networks/

15. CNN
Image Sources:
https://adeshpande3.github.io/A-Beginner%27s-Guide-To-Understanding-Convolutional-Neural-Networks/

17. Image Segmentation
From CNN to FCN
Image Sources:
http://cvlab.postech.ac.kr/research/deconvnet/

19. Urban feature extraction from imagery

20. Self driving cars

21. Asset management

22. Precision Ag

23. Time series forecasting

24. Recommendation engines

25. KEEPINTOUCH
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