Machine learning workshop, session 8. - Artificial Intelligence and Industry - Deep Learning - Demos - Video

1. Machine Learning
Lunch & Learn - Session 8
Luis Borbon
25/07/2017

2. Table of contents
1. Recap
2. AI and Industry
3. Deep Learning
4. Demos
5. Video
6. More Resources

3. Recap

4. Gradient descent
Gradient descent is a first-order iterative
optimization algorithm for finding the
minimum of a function.

5. Gradient descent

6. Gradient descent
Gradient descent is a popular method in the field
of machine learning because part of the process
of machine learning is to find the highest
accuracy, or to minimize the error rate, given a
set of training data.
Gradient descent is used to find the minimum
error by minimizing a "cost" function.

7. Neuron
The artificial neuron receives one or more inputs
(representing dendrites) and sums them to
produce an output (or activation) (representing a
neuron's axon).
Usually the sums of each node are weighted,
and the sum is passed through a non-linear
function known as an activation function.

8. Artificial Neural Network

9. AI and Business

10. Why Tesla Is Worth More Than GM

12. Smartest Companies 2017

13. 50 Smartest Companies
1. Nvidia
2. SpaceX
3. Amazon
4. 23andMe
5. Alphabet
6. iFlytek
7. Kite Pharma
8. Tencent
9. Regeneron
10. Spark Therapeutics
11. Face ++
12. First Solar
13. Intel
14. Quanergy Systems
15. Vestas Wind Systems
16. Apple
17. Merck
18. Carbon
19. Desktop Metal
20. Ionis Pharmaceuticals

14. Deep Learning

15. Deep Learning
Deep learning (also known as deep
structured learning or hierarchical learning)
is the application of artificial neural networks
(ANNs) to learning tasks that contain more
than one hidden layer. Deep learning is part
of a broader family of machine learning
methods based on learning data
representations, as opposed to task-specific
algorithms. Learning can be supervised,
partially supervised or unsupervised.

16. AI vs ML vs DL
Artificial Intelligence: Computer system(s) that mimics and/or replicates human
intelligence.
Machine Learning: Allows computers to learn on their own.
Deep Learning: Algorithms attempting to model high level abstractions in data to
determine a high level meaning.

18. http://www.escience.cn/people/JunweiHan/SaliencyDetection.html

25. Demos

26. Demo
Neural network
https://www.clarifai.com/demo
https://erkaman.github.io/regl-cnn/src/demo.html
http://yann.lecun.com/exdb/lenet/index.html
https://aiexperiments.withgoogle.com
http://nlp.stanford.edu:8080/sentiment/rntnDemo.html

27. Video

28. Video
Check out this video
https://youtu.be/1G0e-mR9a4k

29. More resources

30. Resources
Udacity
Udemy
Coursera
Edx
Your favorite search engine...