Funcionamiento de modelos neuronales, componenentes que lo soportan y algunos consejos de implementación.

1. C O R E M L A N D
C O M P U T E R V I S I O N
@ M I L L A N I M I X

2. H U N I M I X U U K M U WA N
L E O N A R D O - I S R A E L M I L L Á N - G A R C Í A @millanimix
• Mexicano, Tenochca, SkyAnahuacwalker
• Student of the Pre-Hispanic Tradition
• Rusty Researcher of Computer Vision
• Objective-C developer (Oldie but goodie)
• ¡Ah! I currently work as Project Manager

3. C O R E M L
• Integrate machine
learning models into your
app.
• A trained model is the
result of applying a
machine learning
algorithm to a set of
training data.
• The model makes
predictions based on new
input data.
https://developer.apple.com/documentation/coreml

4. E X A M P L E
Link example

5. H O W D O I T D O ?
C O R E M L

6. C O R E M L
• Core ML Supports:
• Image analysis.
• Foundation NLP.
• Learned decision
trees.
https://developer.apple.com/documentation/coreml

7. V I S I O N
N AT U R A L V S A R T I F I C I A L
6 to 7 millions of cones
120 millions of rods
iPhone X 12MP

8. V I S I O N F R A M E W O R K
C O M P U T E R V I S I O N

9. V I S I O N F R A M E W O R K
• Still Image Analysis.
• Image Sequence
Analysis.
• Object Tracking.
• Rectangle Detection.
• Face Detection.
• Barcode Detection.
• Text Detection.
• Horizon Detection.
• Image Alignment.
• Machine-Learning
Image Analysis.
• Coordinate
Conversion.

10. C O R E M L
• Core ML Tools: Python package
• Machine learning models
(.mlmodel):
• Neural networks.
• Tree ensembles.
• Support vector machines.
• Generalized linear models.
• Takes advantages of the CPU
and GPU

11. C O R E M L
• BNNS (Basic Neural Network
Subroutines)
• Accelerate Framework: A
collection of math functions.
• CPU’s fast vector
instructions.
• MPSCNN: Metal Performance
Shaders - Convolutional Neural
Networks
• Compute kernels that run
on the GPU
https://developer.apple.com/documentation/coreml

12. L E A R N I N G

13. N E U R A L N E T W O R K
H U M A N

14. N E U R A L N E T W O R K
A R T I F I C I A L

15. H U M A N N E U R A L N E T W O R K S
• Neuron
• Electrically excitable cell.
• Receives, processes and
transmits information
through electrical and
chemical signals.
• Human Brain
• 1508 g.
• 86 billion neurons.

16. A R T I F I C I A L N E U R A L N E T W O R K S
• Input layer
• Hidden layers
• Output layer

17. A 1 1 B I O N I C
H A R D WA R E

18. A 1 1 B I O N I C
• System on a Chip (SoC).
• 64-bit ARM / 4.3 billion
transistors.
• iPhone 8 / Plus & X.
• Two performance cores /
Four high-efficiency cores.
• Apple-designed GPU with
three-core design.

21. S U M M A RY
A R T I F I C I A L I N T E L L I G E N C E

22. S U M M A RY
A R T I F I C I A L I N T E L L I G E N C E

23. Q U E S T I O N S ?