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Core ML and Computer Vision

NSCoder Mexico
NSCoder Mexico

Funcionamiento de modelos neuronales, componenentes que lo soportan y algunos consejos de implementaci坦n.

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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
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 N - G A R C A @millanimix Mexicano, Tenochca, SkyAnahuacwalker Student of the Pre-Hispanic Tradition Rusty Researcher of Computer Vision Objective-C developer (Oldie but goodie) 臓Ah! I currently work as Project Manager
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
E X A M P L E Link example
H O W D O I T D O ? C O R E M L
C O R E M L Core ML Supports: Image analysis. Foundation NLP. Learned decision trees. https://developer.apple.com/documentation/coreml
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
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
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.
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
C O R E M L BNNS (Basic Neural Network Subroutines) Accelerate Framework: A collection of math functions. CPUs fast vector instructions. MPSCNN: Metal Performance Shaders - Convolutional Neural Networks Compute kernels that run on the GPU https://developer.apple.com/documentation/coreml
L E A R N I N G
N E U R A L N E T W O R K H U M A N
N E U R A L N E T W O R K A R T I F I C I A L
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.
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
A 1 1 B I O N I C H A R D WA R E
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.
Core ML and Computer Vision
Core ML and Computer Vision
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
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
Q U E S T I O N S ?

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Core ML and Computer Vision

  • 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 N - G A R C A @millanimix Mexicano, Tenochca, SkyAnahuacwalker Student of the Pre-Hispanic Tradition Rusty Researcher of Computer Vision Objective-C developer (Oldie but goodie) 臓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. CPUs 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 ?