Use Machine Learning in your code, without being a ML expert

on YouTube ↗42m

" summary

Demonstrates how Google Cloud AutoML plus Google pre-trained APIs let developers add image, text, audio and video intelligence without being ML experts: use cloud vision, cloud natural language, cloud speech-to-text, text-to-speech and cloud video intelligence as REST APIs; use TensorFlow and Cloud Machine Learning Engine for fully custom models; AutoML trains a model from as little as 10 images per label, offers one hour free training in alpha, and returns precision and recall per label so you can iterate.

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" chapters (60)

1. 0:00Introduction
2. 0:57Machine Learning Details
3. 1:15What is Machine Learning
4. 2:15Types of Problems
5. 2:38Example
6. 3:12Problem
7. 3:23Complexity
8. 3:55When did ML start
9. 4:15Google repository
10. 4:59make ML easy
11. 5:14ML spectrum
12. 5:41Custom ML tasks
13. 6:44Overview
14. 6:54General Models
15. 7:10REST API
16. 7:25Cloud Vision
17. 9:15Demo
18. 10:01Face Detection
19. 10:38Natural Language
20. 10:53Analyze Syntax
21. 11:21Classification Content
22. 11:38Calling the API
23. 11:57What is the reply
24. 12:51Speechtotext
25. 13:45How to call
26. 14:11Texttospeech
27. 15:20Generated text
28. 15:31Audio file
29. 16:25Classification
30. 16:50Google suggestion
31. 17:06Tensorflow
32. 17:31Cloud ML Engine
33. 18:32Predict Weather Transfer
34. 18:55Identify Clouds
35. 19:54Workflow
36. 20:58ImageNet
37. 22:16OMalley
38. 22:50Alpha
39. 23:10Cloud
40. 23:24Storage
41. 23:39Labels
42. 24:44Data Set
43. 25:15Free Model
44. 25:44Evaluation
45. 26:18Precision Recall
46. 27:01Predict
47. 27:13Simple program
48. 27:49When to use AutoML Vision
49. 28:39AutoML Vision in other fields
50. 29:21Recap
51. 29:35Pretrained API
52. 29:59Links
53. 30:13Google Developer Community
54. 30:34Questions
55. 33:31Model name
56. 34:55Model parameters
57. 35:17What is better the model
58. 37:44Video Intelligence
59. 39:18Dog Detection
60. 39:34Visual API

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