Ricardo Coelho
March 08, 2017
83

# Introduction to Machine Learning

Learn what is Machine Learning and how data is changing the world faster and faster. This is the era of information at the speed of light. Blink and you're gone.

March 08, 2017

## Transcript

1. Machine Learning
Ricardo Coelho

@ramcoelho

2. Artiﬁcial Intelligence

3. Algorithm

4. Learning

5. People learn from EXPERIENCE

6. Machines learn from DATA

7. How much data?
• A LOT!!
• Big Data
• Text, Image, Audio, Video, Database, Spreadsheets
• AI, Narrow AI, Deep Learning
• Neural Network

8. How much data?
• A LOT!!
• Big Data
• Text, Image, Audio, Video, Database, Spreadsheets
• AI, Narrow AI, Deep Learning
• Neural Network
• Statistics

9. Freakonomics

10. Statistics
Data Relations
Probability
Future
Data Values
Reality
Past and Present

11. Inferential Algorithms
• Regression
• Anomaly Detection
• Clustering
• Classiﬁcation

12. Regression
Find about the future based on the
relationship between variables

PREDICT

13. Anomaly Detection
Identify rare behavior

UNUSUAL

14. Clustering
Separate intuitive groups

STRUCTURE

15. Algorithms (Clustering)

16. Classiﬁcation
Find a category for information.
Decision Tree, Data Mining

TAG

17. Algorithms

18. Supervised learning

19. Genetic/Evolutive Algorithms
https://bit.do/evolutionsim

20. Unsupervised learning

21. Want to tag yourself?
Yes . No

22. Reinforcement learning

23. Udacity - Intro to Machine Learning (2-3 mo)
https://br.udacity.com/course/intro-to-machine-learning--ud120/

24. scikit-learn (sklearn)
>>> import numpy as np
>>> X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
>>> Y = np.array([1, 1, 1, 2, 2, 2])
>>> from sklearn.naive_bayes import GaussianNB
>>> clf = GaussianNB()
>>> clf.fit(X, Y)
GaussianNB(priors=None)
>>> print(clf.predict([[-0.8, -1]]))
[1]

25. PHP-ML
https://github.com/php-ai/php-ml

26. TensorFlow

27. TensorFlow
https://youtu.be/oZikw5k_2FM

28. Restrict vs General AI

29. Thank you!

30. Questions?