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
   

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2. Artificial Intelligence
   

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3. Algorithm
   

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4. Learning
   

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5. People learn from EXPERIENCE
   

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6. Machines learn from DATA
   

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

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

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11. Freakonomics
    

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

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

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14. Regression
    Find about the future based on the
    relationship between variables
    
    PREDICT
    

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15. Anomaly Detection
    Identify rare behavior
    
    UNUSUAL
    

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16. Clustering
    Separate intuitive groups
    
    STRUCTURE
    

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17. Algorithms (Clustering)
    

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

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19. Algorithms
    

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20. Supervised learning
    

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

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22. Unsupervised learning
    

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23. Want to tag yourself?
    Yes . No
    

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24. Reinforcement learning
    

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

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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]
    

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

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29. TensorFlow
    

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

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31. Restrict vs General AI
    

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38. Thank you!
    

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39. Questions?
    

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