• Урок 1. 00:04:01
    Course Introduction
  • Урок 2. 00:01:32
    Extensions on VS Code used in Course
  • Урок 3. 00:02:48
    Installing Flutter on Mac & Windows
  • Урок 4. 00:06:32
    Simple NN - Building a Sign Language Detector in Teachable Machine
  • Урок 5. 00:00:34
    CatvsDog Detector App Review
  • Урок 6. 00:03:13
    Introduction
  • Урок 7. 00:07:44
    Importing assets & Configuring Project
  • Урок 8. 00:04:23
    Setting up Home - Part 1
  • Урок 9. 00:07:49
    Setting up Home - Part 2
  • Урок 10. 00:09:52
    Getting Dataset & Teachable Machine
  • Урок 11. 00:08:20
    Adding TFLite functions in Flutter project
  • Урок 12. 00:02:18
    Taking Photo & Gallery Image Functionality
  • Урок 13. 00:06:11
    Adding Logic to app & Finalizing
  • Урок 14. 00:00:56
    Introduction
  • Урок 15. 00:04:52
    Setting up the Project
  • Урок 16. 00:11:20
    Setting up Home - Part 1
  • Урок 17. 00:02:30
    Setting up Home - Part 2
  • Урок 18. 00:05:22
    Setting up Home - Part 3
  • Урок 19. 00:02:44
    Google Collab Introduction
  • Урок 20. 00:11:16
    Preprocessing our Data
  • Урок 21. 00:15:06
    Building our Neural Network & Exporting it
  • Урок 22. 00:04:27
    Finishing and Testing our app!
  • Урок 23. 00:00:51
    IFruit App Review
  • Урок 24. 00:02:00
    Introduction & Setting up the Project
  • Урок 25. 00:03:39
    Setting up Home
  • Урок 26. 00:04:36
    Getting Dataset & Starting new Notebook
  • Урок 27. 00:07:04
    Building our Neural Network - Part 1
  • Урок 28. 00:06:26
    Building our Neural Network - Part 2
  • Урок 29. 00:01:19
    Sentiment Analysis App Review
  • Урок 30. 00:06:43
    Introduction & Setting up the Project
  • Урок 31. 00:04:26
    Setting up Home - Part 1
  • Урок 32. 00:05:41
    Setting up Home - Part 2
  • Урок 33. 00:04:19
    Setting up Home - Part 3
  • Урок 34. 00:11:07
    Set up functions for API in Flutter App
  • Урок 35. 00:09:57
    Implement API in Flutter App & Finalizing
  • Урок 36. 00:07:56
    Introduction & Setting up the Project
  • Урок 37. 00:06:20
    Setting up Home - Part 1
  • Урок 38. 00:06:31
    Setting up Home - Part 2
  • Урок 39. 00:05:01
    Creating Functions in Home
  • Урок 40. 00:05:33
    Connecting to API Service Red Hat
  • Урок 41. 00:10:07
    Fetching Response
  • Урок 42. 00:08:35
    Adding Logic & Testing API
  • Урок 43. 00:12:38
    Live Camera Functionality - Part 1
  • Урок 44. 00:15:59
    Live Camera Functionality - Part 2 & Finalizing
  • Урок 45. 00:03:29
    Introduction & Setting up the Project
  • Урок 46. 00:06:14
    Setting up Home
  • Урок 47. 00:09:15
    Drawing functionality - Part 1
  • Урок 48. 00:06:32
    Drawing functionality - Part 2
  • Урок 49. 00:16:51
    Saving User Sketch
  • Урок 50. 00:01:39
    Clear Sketch Functionality
  • Урок 51. 00:06:32
    Adding Logic & New Screen
  • Урок 52. 00:11:06
    Building our Neural Network
  • Урок 53. 00:08:49
    Going over Pix2Pix Algorithm & Training
  • Урок 54. 00:04:09
    Reviewing our Neural Network
  • Урок 55. 00:06:27
    Flask Introduction
  • Урок 56. 00:16:08
    Building a Flask Server to Deploy our Neural Network
  • Урок 57. 00:14:51
    Building our API for Flask
  • Урок 58. 00:15:03
    Interacting with Flask & Debugging
  • Урок 59. 00:06:24
    Adding library image as input!
  • Урок 60. 00:02:29
    Finding a larger Edges2Shoes dataset & other Pix2Pix Datasets!
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