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.

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
10. How much data? • A LOT!! • Big Data • Text, Image, Audio, Video, Database, Spreadsheets • AI, Narrow AI, Deep Learning • Neural Network • Statistics
11. Freakonomics
12. Statistics Data Relations Probability Future Data Values Reality Past and Present
13. Inferential Algorithms • Regression • Anomaly Detection • Clustering • Classification
14. Regression Find about the future based on the relationship between variables PREDICT
15. Anomaly Detection Identify rare behavior UNUSUAL
16. Clustering Separate intuitive groups STRUCTURE
17. Algorithms (Clustering)
18. Classification Find a category for information. Decision Tree, Data Mining TAG
19. Algorithms
20. Supervised learning
21. Genetic/Evolutive Algorithms https://bit.do/evolutionsim
22. Unsupervised learning
23. Want to tag yourself? Yes . No
24. Reinforcement learning
26. Udacity - Intro to Machine Learning (2-3 mo) https://br.udacity.com/course/intro-to-machine-learning--ud120/
27. 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]
28. PHP-ML https://github.com/php-ai/php-ml
29. TensorFlow
30. TensorFlow https://youtu.be/oZikw5k_2FM
31. Restrict vs General AI
38. Thank you!
39. Questions?