Convolutional neural neworks

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Luis Serrano

Convolutional neural networks Slides for this video: https://www.youtube.com/watch?v=2-Ol7ZB0MmU

Datos y análisis

Luis Serrano
A friendly introduction to
Convolutional Neural Networks
and Image Recognition

Person AlphabetComputer
/ / / !
Simple World

-1 1
1 -1
1 -1
-1 1

/
1 -1 -1 1
-1 1 1 -1
+
+
-
-
+
-+
-
+ - +-
+ - +-
= 4
= -4
+1 +1 +1+1
-1 -1 -1-1
+ + + = 0
+ + + = 0
x x x = 1
x x x = 1

+ -
- +
Image Recognition Classiﬁer
If positive, “”
If negative, “/”

-1 -1
1 -1
1 1
-1 1

/
+
+
-
-
+
-+
-
1 1 -1 1
-1 -1 1 -1
= 2
= -2
+1 -1 +1+1
-1 +1 -1-1
+ - +-
+ - +-

Artiﬁcial Intelligence
- -
- -
- +
+ -
+ -
- -
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- -
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+ -
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+ +
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- -
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+ +
- -
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+ -
+ +
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16 choices

Artiﬁcial Intelligence
+ +
+ +
- +
+ +
+ -
+ +
+ +
+ -
+ +
- +so-so
worse
better
worse
better

Artiﬁcial Intelligence
+ +
+ +
- +
+ +
+ -
+ +
+ +
+ -
+ +
- +so-so
- -
+ +
+ -
- +
+ -
+ -
worse
better!
worse

Artiﬁcial Intelligence
Way too many choices
0.5 1.2
0.7 1.0
0.9 -0.7
-0.6 1.1
, , etc…

Gradient Descent
0.5 1.2
0.7 1.0 0.6 0.9
0.5 1.1
0.7 0.4
0.3 1.2
0.9 -0.2
-0.2 1.1
0.9 -0.7
-0.6 1.1
1 -1
-1 1
Lots of
errors
Derivatives
Few
errors

XOXO!
Slightly More Complex World
Person Alphabet
X O
Computer
X O

1 -1 -1
-1 1 -1
-1 -1 1

-1 -1 1
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1 -1 -1
1 -1 1
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1 -1 1
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/
X
O

X
O
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1 -1 1
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1 -1 1
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-1 -1 1
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1 -1 -1
1 -1 -1
-1 1 -1
-1 -1 1

Convolutional Neural Network
Convolution Layer
Pooling Layer
Fully Connected
Layer

1 -1 1
-1 1 -1
1 -1 1
4 -4
-4 4
+ -
- +
+
+
-
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4 -4
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+ -
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+
Convolution Layer Pooling Layer

-1 1 -1
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1 -1 -1
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2 -4
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+ -
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2 -4
-4 2
+ -
- +
+
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4 -2
- +
+ -
-
-
+
+

Convolution Layer
Pooling Layer
Fully Connected Layer

1 -1 1
-1 1 -1
1 -1 1
-1 1 -1
1 -1 1
-1 1 -1
-1 -1 1
-1 1 -1
1 -1 -1
1 -1 -1
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-1 -1 1
1 -1 -1 1
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-1 1 1 -1
1 -1 -1 1
-1 -1 -1 -1
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-1 -1 -1 -1

1 -1 1
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1 -1 1
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-1 -1 1
1 -1 -1 1
-1 -1 -1 -1
+ - - +
- + + - X
- + + -
+ - - +
- - - -
- + + -
+ - - +
- - - -
O
/

Filters

1 -1 1
-1 1 -1
1 -1 1
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+ - - +
- + + -
- + + -
+ - - +
- - - -
- + + -
+ - - +
- - - -
8X
O
/

-8
4
4
+1 +1 +1+1
+1 +1 +1+1

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1 -1 -1 1
+ - - +
- + + -
- + + -
+ - - +
- - - -
- + + -
+ - - +
- - - -
-8X
O
/

8
-4
-4

-1 -1 1
-1 1 -1
1 -1 -1
-1 -1 -1 -1
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+ - - +
- + + -
- + + -
+ - - +
- - - -
- + + -
+ - - +
- - - -
4X
O
/

-4
8
0

1 -1 -1
-1 1 -1
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1 -1 -1 1
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- + + -
+ - - +
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- + + -
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4X
O
/

-4
0
8

1 -1 1
-1 1 -1
1 -1 1
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1 -1 1
-1 1 -1
-1 -1 1
-1 1 -1
1 -1 -1
1 -1 -1
-1 1 -1
-1 -1 1
X
O
/

Convolutional Neural Network
Convolution Layer
Pooling Layer
Fully Connected
Layer

+ -
- +
+ -
- +
+ -
- +
+ -
- +
- +
+ -
- +
+ -
- +
+ -
- +
+ -
+ - - +
- + + -
- + + -
+ - - +
- - - -
- + + -
+ - - +
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1 -1 -1 1
-1 1 1 -1
-1 1 1 -1
1 -1 -1 1
-1 -1 -1 -1
-1 1 1 -1
1 -1 -1 1
-1 -1 -1 -1
1 -1 1
-1 1 -1
1 -1 1
X
O
/

Convolution Layer Pooling Layer Fully Connected Layer

+ -
- +
+ -
- +
+ -
- +
+ -
- +
- +
+ -
- +
+ -
- +
+ -
- +
+ -
+ - - +
- + + -
- + + -
+ - - +
- - - -
- + + -
+ - - +
- - - -
1 -1 -1 1
-1 1 1 -1
1 -1 1
-1 1 -1
1 -1 1
X
O
/

Convolution Layer Pooling Layer Fully Connected Layer
8
-8
4
4

Gradient Descent
X O
Lots of
errors
Few
errors

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https://www.youtube.com/c/LuisSerrano
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1. Luis Serrano A friendly introduction to Convolutional Neural Networks and Image Recognition

2. Person AlphabetComputer / / / ! Simple World

3. Simple World 1 11 1

4. Simple World /

5. Keyboard

6. Image recognition software /

7. -1 1 1 -1 1 -1 -1 1 / 1 -1 -1 1 -1 1 1 -1 + + - - + -+ - + - +- + - +- = 4 = -4 +1 +1 +1+1 -1 -1 -1-1 + + + = 0 + + + = 0 x x x = 1 x x x = 1

8. + - - + Image Recognition Classiﬁer If positive, “” If negative, “/”

9. -1 -1 1 -1 1 1 -1 1

10. -1 -1 1 -1 1 1 -1 1 / + + - - + -+ - 1 1 -1 1 -1 -1 1 -1 = 2 = -2 +1 -1 +1+1 -1 +1 -1-1 + - +- + - +-

11. Artiﬁcial Intelligence ? = = / + - - +

12. Artiﬁcial Intelligence - - - - - + + - + - - - - + - + - + - - - - + - - - + + + + + - - - - + + + - - + - + - + - - + + + - + + - + + - + + + + + + + 16 choices

13. Artiﬁcial Intelligence + + + + so-so

14. Artiﬁcial Intelligence + + + + - + + + + - + + + + + - + + - +so-so worse better worse better

15. Artiﬁcial Intelligence + + + + - + + + + - + + + + + - + + - +so-so - - + + + - - + + - + - worse better! worse

16. Artiﬁcial Intelligence Way too many choices 0.5 1.2 0.7 1.0 0.9 -0.7 -0.6 1.1 , , etc…

17. Gradient Descent 0.5 1.2 0.7 1.0 0.6 0.9 0.5 1.1 0.7 0.4 0.3 1.2 0.9 -0.2 -0.2 1.1 0.9 -0.7 -0.6 1.1 1 -1 -1 1 Lots of errors Derivatives Few errors

18. XOXO! Slightly More Complex World Person Alphabet X O Computer X O

19. 1 -1 -1 -1 1 -1 -1 -1 1 -1 -1 1 -1 1 -1 1 -1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 / X O

20. 1 -1 1 -1 1 -1 1 -1 1 + + - - + - + - +

21. 1 -1 -1 1 Previous Knowledge -1 1 1 -1

22. X O / 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 -1 -1 1 -1 1 -1 1 -1 -1 1 -1 -1 -1 1 -1 -1 -1 1 Convolutional Neural Network Convolution Layer Pooling Layer Fully Connected Layer

23. 1 -1 1 -1 1 -1 1 -1 1 4 -4 -4 4 + - - + + + - - -4 4 4 -4 - + + - - - + + Convolution Layer Pooling Layer

24. 1 -1 1 -1 1 -1 1 -1 1

25. -1 1 -1 1 -1 1 -1 1 -1 -4 4 4 -4 + - - + + + - - 4 -4 -4 4 - + + - - - + +

26. -1 1 -1 1 -1 1 -1 1 -1

27. 1 -1 -1 -1 1 -1 -1 -1 1 4 -2 -2 4 + - - + + + - - -4 2 2 -4 - + + - - - + +

28. 1 -1 -1 -1 1 -1 -1 -1 1

29. -1 -1 1 -1 1 -1 1 -1 -1 2 -4 -4 2 + - - + + + - - -2 4 4 -2 - + + - - - + +

30. -1 -1 1 -1 1 -1 1 -1 -1

31. Convolution Layer Pooling Layer Fully Connected Layer

32. 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 -1 -1 1 -1 1 -1 1 -1 -1 1 -1 -1 -1 1 -1 -1 -1 1 1 -1 -1 1 -1 1 1 -1 -1 1 1 -1 1 -1 -1 1 -1 -1 -1 -1 -1 1 1 -1 1 -1 -1 1 -1 -1 -1 -1

33. 1 -1 1 -1 1 -1 1 -1 1 1 -1 -1 1 -1 1 1 -1 -1 1 -1 1 -1 1 -1 1 -1 -1 1 1 -1 1 -1 -1 1 -1 -1 1 -1 1 -1 1 -1 -1 -1 -1 -1 -1 -1 1 1 -1 1 -1 -1 -1 1 -1 -1 -1 1 1 -1 -1 1 -1 -1 -1 -1 + - - + - + + - X - + + - + - - + - - - - - + + - + - - + - - - - O / Filters

34. 1 -1 1 -1 1 -1 1 -1 1 1 -1 -1 1 -1 1 1 -1 + - - + - + + - - + + - + - - + - - - - - + + - + - - + - - - - 8X O / -8 4 4 +1 +1 +1+1 +1 +1 +1+1

35. -1 1 -1 1 -1 1 -1 1 -1 -1 1 1 -1 1 -1 -1 1 + - - + - + + - - + + - + - - + - - - - - + + - + - - + - - - - -8X O / 8 -4 -4

36. -1 -1 1 -1 1 -1 1 -1 -1 -1 -1 -1 -1 -1 1 1 -1 + - - + - + + - - + + - + - - + - - - - - + + - + - - + - - - - 4X O / -4 8 0

37. 1 -1 -1 -1 1 -1 -1 -1 1 1 -1 -1 1 -1 -1 -1 -1 + - - + - + + - - + + - + - - + - - - - - + + - + - - + - - - - 4X O / -4 0 8

38. 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 -1 -1 1 -1 1 -1 1 -1 -1 1 -1 -1 -1 1 -1 -1 -1 1 X O / Convolutional Neural Network Convolution Layer Pooling Layer Fully Connected Layer

39. + - - + + - - + + - - + + - - + - + + - - + + - - + + - - + + - + - - + - + + - - + + - + - - + - - - - - + + - + - - + - - - - 1 -1 -1 1 -1 1 1 -1 -1 1 1 -1 1 -1 -1 1 -1 -1 -1 -1 -1 1 1 -1 1 -1 -1 1 -1 -1 -1 -1 1 -1 1 -1 1 -1 1 -1 1 X O / Convolution Layer Pooling Layer Fully Connected Layer

40. + - - + + - - + + - - + + - - + - + + - - + + - - + + - - + + - + - - + - + + - - + + - + - - + - - - - - + + - + - - + - - - - 1 -1 -1 1 -1 1 1 -1 1 -1 1 -1 1 -1 1 -1 1 X O / Convolution Layer Pooling Layer Fully Connected Layer 8 -8 4 4

41. X O Artiﬁcial Intelligence ?

42. Gradient Descent X O Lots of errors Few errors

43. People Computer Alphabet Advanced World

44.

45.

46. http://serrano.academy https://www.linkedin.com/in/luisgserrano https://www.youtube.com/c/LuisSerrano Twitter: luis_likes_math Subscribe, like, share, comment

Convolutional neural neworks

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