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YGLF_2019.pdf

 YGLF_2019.pdf

Bbc0c41f72dffc7701986e7ef58e3bbe?s=128

Asim Hussain

April 05, 2019
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  1. The Future of Machine Learning & JavaScript @jawache YGLF 2019

  2. Asim Hussain @jawache codecraft.tv microsoft.com

  3. https://aka.ms/jawache-cda @jawache

  4. @jawache https://www.palinternship.com/

  5. @jawache

  6. Asim Web Development Machine Learning This is @EleanorHaproff's slide

  7. None
  8. @jawache

  9. TheMojifier™ @jawache

  10. None
  11. @jawache themojifier.com

  12. None
  13. How to Calculate Emotion? @jawache

  14. (1) Detect Facial Features @jawache

  15. https://towardsdatascience.com/facial-keypoints-detection-deep-learning-737547f73515

  16. (2) Use a Neural Network @jawache

  17. Neural Networks Axon Dendrites Axons Body @jawache

  18. 1 23 8.6 -0.5 2.1 Activation Function @jawache Neural Networks

  19. 1 23 8.6 -0.5 2.1 x x activation(...) = -11.5

    = 18.06 7.01 !-> !-> } @jawache Neural Networks
  20. Output 0 0 1 Input @jawache Neural Networks

  21. 1.1 4.2 0.3 4 12 93 3 @jawache Neural Networks

  22. 1.1 4.2 0.3 4 12 93 @jawache 8 - 8

    = -5 3 Neural Networks
  23. 1.1 4.2 0.3 4 12 93 @jawache - 8 =

    -5 3 8 Neural Networks
  24. 0.1 9.2 0.2 4 12 93 @jawache 8 8 Neural

    Networks
  25. @jawache https://azure.microsoft.com/services/cognitive-services/face/

  26. https:!//<region>.api.cognitive.microsoft.com/face/v1.0/detect { "url": "<path-to-image>" } @jawache

  27. @jawache

  28. Summary @jawache

  29. • Neural Networks are incredibly powerful • Conceptually, they are

    simple to understand @jawache Summary
  30. TensorFlow, MobileNet & I'm fine @jawache

  31. @jawache

  32. @jawache

  33. @jawache

  34. TensorFlow.js @jawache

  35. TensorFlow.js Train models Load pre-trained models @jawache

  36. https://github.com/tensorflow/tfjs-models @jawache MobileNet

  37. https://azure.microsoft.com/services/cognitive-services/computer-vision/ @jawache

  38. https://codepen.io/sdras/full/jawPGa/ @jawache

  39. @jawache https://twitter.com/ollee/status/930303340516216832

  40. @jawache https://twitter.com/FrontendNE/status/930120267992616960

  41. @jawache https://twitter.com/chrispiecom/status/930407801402347520

  42. Summary @jawache

  43. • TensorFlow.js doesn't have any dependancies • MobileNet is a

    simple way to analyse images • Azure Computer Vision API ❤ @jawache Summary
  44. Image2Image @jawache

  45. DEMO @jawache https://zaidalyafeai.github.io/pix2pix/cats.html

  46. @jawache Generator Discriminator ✅ ❌

  47. @jawache Generator Discriminator ✅ ❌

  48. @jawache Generator Discriminator ✅ ✅

  49. @jawache

  50. @jawache

  51. @jawache

  52. @jawache https://github.com/NVIDIA/vid2vid

  53. @jawache https://github.com/NVIDIA/vid2vid

  54. @jawache https://github.com/NVIDIA/vid2vid

  55. @jawache https://github.com/hanzhanggit/StackGAN

  56. Summary @jawache

  57. • GANs learn to generate new images • They take

    a lot of compute to train • But the generator model can be run in the browser @jawache Summary
  58. @jawache aka.ms/mojifier

  59. Asim Hussain @jawache codecraft.tv microsoft.com