Dive into Deep Learning with Scala

on YouTube ↗39m

" summary

Scala code uses TensorFlow for Scala to train on 800 labeled Scala Days photos and iterates from a simple fully connected net (~75–80% test accuracy) to a convolutional model (one 2D conv layer with 32 3×3 filters, bias, activation and max‑pool) running on GPU and reaching 95% test accuracy. The workflow shows concrete steps: dataset pipeline, cross‑entropy loss, gradient descent optimizer, batch training, and deployable model (live demo was flaky but screenshots confirm results).

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" chapters (48)

1. 0:00Intro
2. 0:33Electricity
3. 1:08Deep Learning
4. 1:40Getting Started
5. 2:27Theres no free lunch
6. 2:48Deep Learning in 3 Steps
7. 3:09What is Deep Learning
8. 3:54Computer Vision
9. 4:45Speech Recognition
10. 5:06Machine Translation
11. 5:29What do these examples have in common
12. 6:02Overlaying the examples
13. 6:21Generic functions
14. 6:48Models
15. 7:02Classifiers
16. 7:26Tensors
17. 7:55Tensor Models
18. 8:33Artificial Neuron
19. 10:47Architecture
20. 11:51Machine Learning
21. 13:14Training Data Examples
22. 14:00How Does Training Work
23. 14:19First Step
24. 15:04BackPropagation
25. 15:33Gradient Descent
26. 16:36Why Deep Learning Works
27. 17:14Composition
28. 18:28Narrow Intelligence
29. 19:23Conclusion
30. 19:38Why Scala
31. 20:39Type Safety
32. 21:37What features should a deep learning library provide
33. 22:43Three deep learning libraries
34. 24:25Example code
35. 25:44Look for Existing Solutions
36. 26:27Supervised Learning
37. 27:46Data Source
38. 28:51Architectures
39. 30:01Convolutional
40. 31:03Neural Network
41. 31:37Model Building
42. 34:19Training
43. 35:19Training with more neurons
44. 35:59convolutional layer
45. 36:36network classifier
46. 37:06run model
47. 37:38deployment
48. 38:31main takeaways

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