You will be introduced to the concepts of Artificial Intelligence, Machine Learning, and Deep Learning.

1. AI DEMO
BATTERY RECOGNIZER
PRESENTED BY WING CHAN

2. AGENDA
•AI vs Machine Learning vs Deep Learning
•Azure Cognitive Services
•Demo – Battery Recognizer
•Lessons Learn
•Q&A

3. AI = THINKING MACHINE?

4. AI = DATA

5. AI VS MACHINE LEARNING VS DEEP LEARNING

6. MACHINE LEARNING

7. SUPERVISED VS UNSUPERVISED

8. REINFORCEMENT LEARNING

9. MACHINE LEARNING VS DEEP LEARNING

10. ARTIFICIAL NEURAL NETWORK IN DEEP LEARNING

11. COMPARISON AND WHICH ONE TO PICK?
Machine Learning Deep Learning
Amount of Data Small Big
Features Define your own Learns automatically
Time Short Long
Accuracy Good Best
Debugging Easy Very Tough
Expensive Less More
Decision Path Yes No

12. MACHINE LEARNING WORKFLOW

13. AZURE COGNITIVE SERVICES

14. DEMO – BATTERY RECOGNIZER
• Embedded the
exported
models to your
iOS and
Android apps
Use Your
Models
• Export CoreML
and TensorFlow
models for
offline usage
Export
Models
• Generate a
trained
model by
training model
Training
Model
• Tags battery
images per
battery model
types
Classification
• Upload Battery
Images
Input data
• Create Custom
Vision Service
in Azure
Cognitive
services
Setup
Service

15. LESSONS LEARN
• Leverage AI platforms like Azure Cognitive Services to create your
own ML models easily
• Support offline ML model's implementation for better UX and privacy
but may decrease the accuracy.
• "Data, Data, DATA" - the key for creating high accurate ML models
• Evaluate your ML models results continuously to improve performance

16. QUESTIONS?
Demo App Source code
https://goo.gl/AcY2Qd