Making Android Apps with Intelligence
summary
Overview of concrete capabilities and failures: demos use Google Play services Awareness API to combine time location activity places beacons and weather, and the mobile vision API for face landmarks eye open/blink smiling plus barcode and text recognition; cloud REST APIs (Google Cloud, Microsoft Cognitive Services, IBM Watson, HP) return age gender emotion and labels; Alexa on Raspberry Pi and Pepper robot get built; on‑device TensorFlow on device runs without network but cloud calls fail when offline; note permission and privacy risks.
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chapters (24)
- 0:00Start
- 1:29What Is Machine Learning
- 3:29Google Play Services
- 4:10Awareness Api
- 7:32Text Recognizer
- 8:03Face Mobile Vision Api
- 10:09Face Trucker
- 12:51Google Machine Learning Services
- 13:49Microsoft Cognitive Services Api
- 17:17Challenges
- 18:15Demo of an App
- 18:44Vision Api
- 19:15Microsoft Language Understanding Intelligence Service
- 20:23Machine Learning Services
- 20:48Google Cloud Machine Learning Platform
- 21:18Google Tensorflow
- 21:49Example App with Tensorflow
- 24:28Train Alexa
- 25:41Pepper the Robot
- 26:11Get Started Programming Robots
- 27:41Design Considerations
- 28:29Ease of Use
- 30:40Data Privacy
- 31:06What Is Next
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