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Some insights & Deep Learning in a nutshell

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My personal experience working as a data science for a Canadian startup applying deep learning for medical diagnosis.

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Some insights & Deep Learning in a nutshell

  1. 1. Some insights & Deep Learning in a nutshell By Adrià Romero October 2017
  2. 2. hello! I am Adrià Romero And I was concern about my future. You can find me at:
  3. 3. ContentMotivation Time Dropout school Hobby 1st 2nd 3rd 4th school 1. My experience at school 2. Deep Learning 3. My experience at industry
  4. 4. 1. My Experience at School Ideas Incubator
  5. 5. FUTURE DECISIONS
  6. 6. What should I do after School?
  7. 7. Ideas Incubator ★ Lab practices ★ Group projects ★ Exams ★ Personal webpage ★ Social media ★ Google Scholar ★ ResearchGate ★ LinkedIn ★ GitHub- BSc THESIS
  8. 8. My BSc Thesis ★ Deep Learning + ★ Florida Atlantic University + ★ Skin Disease Diagnosis
  9. 9. After school A Survival Guide to a PhD [NEW!] Industry PhD
  10. 10. 2. Deep Learning The present (and future) of AI
  11. 11. MOTIVATION Multimedia data Growth
  12. 12. MOTIVATION Global Mobile Data Traffic Source: Cisco Visual Networking Index 1 EB = 1018 B
  13. 13. MOTIVATION Data science job [More analytics]
  14. 14. Tools to extract Knowledge from data
  15. 15. STATE-OF-THE-ART HIERARCHY
  16. 16. WHAT IS DEEP LEARNING?
  17. 17. DEEP LEARNING MOTIVATION
  18. 18. MACHINE LEARNING VS DEEP LEARNING
  19. 19. ONE PERCEPTRON TO RULE THEM ALL
  20. 20. ONE PERCEPTRON TO RULE THEM ALL
  21. 21. DEEP LEARNING BASICS Our class label {cat,dog} Artificial Neural Networks CAT DOG
  22. 22. DEEP LEARNING BASICS Artificial Neural Networks Bias term Score function Weights
  23. 23. DEEP LEARNING BASICS Artificial Neural Networks
  24. 24. DEEP LEARNING BASICS Some input vector Our class label Artificial Neural Networks
  25. 25. DEEP LEARNING BASICS Artificial Neural Networks
  26. 26. DEEP LEARNING BASICS Output = input * weights + bias Artificial Neural Networks
  27. 27. DEEP LEARNING BASICS Output = input * weights + bias Artificial Neural Networks
  28. 28. DEEP LEARNING BASICS Output = input * weights + bias Model optimization
  29. 29. DEEP LEARNING BASICS Loss (prediction) = error (prediction, ground_truth) Model optimization ● Loss function ● Objective: minimize loss error ○ Back propagation ■ Find global minimum
  30. 30. BACK PROPAGATION
  31. 31. OPTIMIZERS
  32. 32. DEEP LEARNING ARCHITECTURES
  33. 33. DEEP LEARNING ARCHITECTURES Modern architectures [Deep Residual Learning for Image Recognition, 2015]
  34. 34. DEEP LEARNING ARCHITECTURES Modern architectures [GoogLeNet, Szegedy et al., 2014 ]
  35. 35. DEEP LEARNING BASICS Types of NNs AUTOENCODERS CONVOLUTIONALS RECURRENT MEMORY LSTM GENETIC DYNAMIC GANs
  36. 36. NNs for … TEXT RECURRENT NEURAL NETWORKS
  37. 37. NNs for … AUDIO RECURRENT NEURAL NETWORKS
  38. 38. NNs for … NATURAL LANGUAGE PROCESSING RECURRENT NEURAL NETWORKS
  39. 39. ONE PERCEPTRON TO RULE THEM ALL
  40. 40. NNs for … IMAGE PROCESSING CONVOLUTIONAL NEURAL NETWORKS (CNNs)
  41. 41. CONVOLUTION OPERATOR
  42. 42. CNNs ORIGINS ● CNNs ● Animal Visual Cortex
  43. 43. WHY DEEP LEARNING NOW? Datasets Framework GPUs
  44. 44. WHY DEEP LEARNING NOW?
  45. 45. WHY DEEP LEARNING NOW?
  46. 46. WHY DEEP LEARNING NOW? [NVIDIA et al.]
  47. 47. DEEP LEARNING TAKE OFF
  48. 48. IMAGENET CHALLENGE
  49. 49. CNNs ARCHITECTURE Input image [Yann LeCun et al.]
  50. 50. CNNs ARCHITECTURE [Yann LeCun et al.] 1. Convolutional Layers 2. Activation Layer 3. Pooling Layers
  51. 51. CNNs ARCHITECTURE [Yann LeCun et al.] Fully-Connected Layer
  52. 52. CNNs ARCHITECTURE [Yann LeCun et al.] Output label
  53. 53. MULTI-MODAL TYPES
  54. 54. REAL CASES Learning how to play [Github repo]
  55. 55. REAL CASES Learning how to play (and beat!) [AlphaGo]
  56. 56. REAL CASES Learning how to paint Google DeepDream uses CNNs to find and enhance patterns in images via algorithmic pareidolia Picture: Barcelona, Parc Güellhttp://deepdreamgenerator.com
  57. 57. REAL CASES Learning how to compose music [FlowMachines]
  58. 58. REAL CASES Learning how to write poems Google AI project writes poetry which could make a Vogon proud
  59. 59. REAL CASES Learning how to drive Tesla Autopilot
  60. 60. REAL CASES Learning how to manipulate and move Atlas, de Boston Dynamics
  61. 61. REAL CASES Learning how to diagnose Google DeepMind Health project
  62. 62. REAL CASES Learning how to LEARN? AlphaGo Zero: Learning from scratch
  63. 63. CNNs HANDS-ON ● MNIST dataset ○ Handwritten digits images ○ Training: 60k imgs ○ Validation: 10k imgs ● Keras framework ● 12 epochs ● 97% accuracy model = Sequential() model.add(Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=input_shape)) model.add(Conv2D(64, (3, 3), activation='relu')) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Dropout(0.25)) model.add(Flatten()) model.add(Dense(128, activation='relu')) model.add(Dropout(0.5)) model.add(Dense(num_classes, activation='softmax')) [MNIST dataset]
  64. 64. COURSES RECOMMENDATIONS ● CS231N - Stanford ● Deep Learning Course - Udacity ● Coursera - Andrew Ng DL ● Machine Learning sub-Reddit ● Quora ● Research papers ● Gitxiv
  65. 65. 3. My experience at industry Long live deep learning!
  66. 66. Some final thoughts... ▣ Do not burn down your projects/ideas from school ▣ (Try) to make long term decisions ▣ Go always deeper in everything you do in life
  67. 67. thanks! Any questions? You can find me at adriaromero@me.com

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