Machine learning for front-end developers
summary
Shows concrete, working front-end ML: a live COCO-SSD + TensorFlow.js demo that classifies recyclables from a phone camera, a MobileNet + KNN transfer learning example that trains gestures in ~30 seconds, and a from‑scratch CNN classifier using the QuickDraw dataset (28×28 preprocessing, 80/20 train/test split). Code-level steps (load model, grab webcam pixels, reshape tensors, predict) and limits (model size, mobile battery, demo flakiness) are demonstrated and measured.
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chapters (18)
- 0:00Intro
- 2:48EXAMPLES OF ALGORITHMS
- 3:11TYPES OF MACHINE LEARNING ALGORITHMS
- 3:40SUPERVISED LEARNING
- 7:19GENERATING ALT TEXT
- 7:54FILTERING UNWANTED CONTENT
- 8:59ACCESSIBILITY
- 10:06WHY
- 12:04WHAT CAN YOU DO
- 12:42TOOLS
- 14:08RECYCLING
- 17:25THE TEACHABLE KEYBOARD
- 20:54THE WILLY DETECTOR
- 22:43PROCESS
- 25:10CODE SAMPLE
- 26:28LIMITS
- 28:09ETHICS
- 29:38INSPIRATION
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