Myths and Reality of Android Machine Learning
summary
Practical claims and demos dominate: a Pixel 3 runs live on-device inference for face contours while a Nexus 5X hits about five–ten fps; ML Kit delivers built-in features like face contour and smart replies that return top three–five suggestions and can run on device or in the cloud; transfer learning lets a prototype train in minutes (two to three on a workstation) with as few as ~50 examples per class to get useful results; Android speech and TTS APIs date back to API 8 and 4 respectively.
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chapters (10)
- 0:00Start
- 4:41Thoughtful design helps
- 8:23Use a ready made Ibrary
- 8:36Cross platform support
- 11:31Image Labelling
- 15:233. Use a ready made library...continue
- 18:11Which Android version support this?
- 24:20Follow well understood paths
- 37:03ML needs the right amount of data
- 39:25Does machine learning offer unique value?
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