TensorFlow in your Browser

on YouTube ↗01h 04m

" summary

Shows real training inside the browser using TensorFlow.js (formerly deeplearn.js) with WebGL doing the heavy lifting, including a demo CNN on MNIST that reaches about 92% accuracy (46/50) live in-page. Notes Google Colab offers 12 hours of free GPU per day for heavier work, warns the shipped client is a 35,000-line minified bundle, and recommends Python/TensorFlow for deeper experimentation while JavaScript is viable for in-browser demos and quick iteration.

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" chapters (36)

1. 0:00Start
2. 3:20Highlights/Overview
3. 3:50The Data/Al Landscape
4. 6:42Use Cases for Deep Learning
5. 9:00NN: 2 Hidden Layers (Regression)
6. 10:00NN 3 Hidden Layers: Classifier
7. 18:00Classification and Deep Learning
8. 19:59Euler's Function (e: 2.71828...)
9. 20:16The sigmoid Activation Function
10. 21:53The tanh Activation Function
11. 22:10The ReLU Activation Function
12. 23:01The softmax Activation Function
13. 24:57Activation Functions in Python
14. 26:06Linear Regression in 2D: example
15. 29:35Linear Regression: example #2
16. 33:23Linear Multivariate Analysis
17. 34:43Types of Optimizers
18. 34:55Deep Neural Network: summary
19. 37:18CNNs: Convolution, ReLU, and Max Pooling
20. 38:45CNNs: Convolution Calculations
21. 39:12CNNs: Convolution Matrices (examples)
22. 39:27CNNs: Max Pooling Example
23. 40:27GANS: Generative Adversarial Networks
24. 44:55What is TensorFlow?
25. 47:35TensorFlow Use Cases (Generic)
26. 50:02TensorFlow Graph Execution
27. 50:15TensorFlow "primitive types"
28. 50:48TensorFlow Arithmetic
29. 51:17TF placeholders and feed_dict
30. 52:40TensorFlow: Simple Equation
31. 53:15Saving Graphs for TensorBoard
32. 54:29TensorFlow Eager Execution
33. 54:53What is tensorflow.js?
34. 55:54async keyword
35. 56:13await keyword
36. 59:52Some of my Books 1 HTML5 Canvas and CSS3 Graphics (2013)

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