The 4 steps of Android Machine Learning
summary
Covers concrete, runnable paths: start with the people + AI guidebook for design, use ML Kit for on‑device APIs or pair on‑device object detection with Cloud Vision product search (IKEA case) for live lookup, or grab TF Hub TF‑Lite models (supermarket 100,000 classes, wine 400,000 classes; sizes ~40 MB and ~140 MB). Train with Firebase AutoML Vision Edge or TF‑Lite Model Maker (image, Q&A BERT), and deploy via ML Kit custom models, TF‑Lite Task Library, or Android Studio ML model binding.
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chapters (8)
- 0:00Introduction to Android ML
- 3:48Designing ML in apps
- 5:09Finding existing models
- 11:54MLKit deep dive
- 17:15Building custom models
- 22:13Integrating models into apps
- 37:48Post-deployment ML design
- 40:37Q&A on ML models
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