A Gentle Introduction to Deep Learning for Developers at Abstractions

Like flying cars, the promise of artificial general intelligence (AGI) has been elusive for years. We are a long ways out from machines that can perform intellectual tasks equivalent to that of a human. Deep learning, a subset of machine learning, is a technology available today which enables developers to add narrow artificial intelligence (AI) capabilities to their applications including image or audio classification, facial recognition, object recognition, image caption generation, and natural language processing. We'll explore how developers can integrate pre-trained open source deep learning models into their applications and how developers and data scientists can collaborate on the development, training, and deployment of deep learning models.

Transcript

1. A Gentle Introduction
   to Deep Learning
   for Developers
   —
   Bradley Holt
   Program Manager, Developer Advocacy
   Center for Open-Source Data & AI Technologies
   ↳ (CODAIT)
   @BradleyHolt | @ibmcodait | @IBMDeveloper
   medium.com/codait
   github.com/codait | github.com/IBM
   developer.ibm.com
   

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2. Is AI overhyped?
   Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
   

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3. Yes
   Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
   

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4. Thank you
   for coming
   to my talk
   Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
   

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5. ↳ General Artificial Intelligence
   Metal Skull With Terminator Eye by L.C. Nøttaasen, on Flickr (CC BY-SA 2.0).
   Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
   

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6. ↳ Broad Artificial Intelligence
   -[ electrIc b88Gal88 ]- by JD Hancock, on Flickr (CC BY 2.0).
   Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
   

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7. ↳ Narrow Artificial Intelligence
   Danbo on the Lookout by IQRemix, on Flickr (CC BY-SA 2.0).
   

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8. Approaches to
   Artificial Intelligence
   Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
   Machine Learning
   • Predictive analytics
   • Data mining
   • Anomaly detection
   • Email filtering
   Deep Learning
   • Image or audio
   classification
   • Facial recognition
   • Object recognition
   • Image caption
   generation
   • Natural language
   processing
   

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9. Demo:
   ⬐
   Object identification
   and image segmentation
   with magicat
   
   Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
   

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10. https://www.npmjs.com/package/magicat
    

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11. Install magicat
    $ npm install -g magicat
    + magicat@1.4.9
    added 255 packages from 209 contributors in 11.798s
    

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12. Animal photos by Susanne Nilsson, on Flickr (CC BY-SA 2.0).
    23895621638_535be71dee_k.jpg
    37038669284_899d7784a9_k.jpg
    37489697170_31d05aa027_k.jpg
    37699459356_24fd526a5e_k.jpg
    37699976806_5ce694be36_k.jpg
    

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13. Scan Directory with magicat
    $ magicat . --contains sheep
    Scanning directory '~/tfjs-demos/magicat' for sheep...
    Sheep found in:
    37038669284_899d7784a9_k.jpg
    37489697170_31d05aa027_k.jpg
    

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14. Save Image Segment with magicat
    $ magicat 37699976806_5ce694be36_k.jpg --save horse
    The image '37699976806_5ce694be36_k.jpg' contains the following segments: background, horse.
    saved 37699976806_5ce694be36_k-horse.png
    Animal photos by Susanne Nilsson, on Flickr (CC BY-SA 2.0).
    

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15. Demo:
    ⬐
    Veremin, A Video
    Theremin Based
    on PoseNet
    
    Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    

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16. Untitled by Ash Nowak, on Flickr (CC BY-SA 2.0).
    

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17. ↳ https://veremin.mybluemix.net/
    

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18. ↳ Deep Learning Code Patterns
    https://developer.ibm.com/patterns/category/model-asset-exchange/
    

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19. Software
    Programming
    Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    Untitled by Marcin Wichary, on Flickr (CC BY 2.0).
    

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20. Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    01011001001011000001
    10101101010100100110
    00010110101010011100
    10101010110101010100
    10001001011101000101
    Software Program
    Business Logic
    

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21. Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    01011001001011000001
    10101101010100100110
    00010110101010011100
    10101010110101010100
    10001001011101000101
    Software Program
    Input
    Program Execution
    Output
    

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22. Machine Learning vs.
    Software Programming
    Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    Machine Learning
    • Training
    • High-quality examples
    (i.e., training data)
    • Approximation of a
    correct function
    Software Programming
    • Programming
    • Set of direct
    instructions
    • Precisely-defined
    function
    

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23. Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    Input Layer Hidden Layers Output Layer
    

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24. Backpropagation
    Labeled Training Data
    Coat
    Sneaker
    T-shirt Sneaker
    Pullover
    Output Errors
    Pullover
    Coat
    Coat
    Sneaker T-shirt
    ❌
    ❌ ❌
    Fashion-MNIST dataset by Zalando Research, on GitHub (MIT License).
    

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25. Input Output
    Sneaker
    98%
    Neural Network Inferencing
    Fashion-MNIST dataset by Zalando Research, on GitHub (MIT License).
    

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26. Machine
    Learning
    Libraries
    Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    Untitled by Marcin Wichary, on Flickr (CC BY 2.0).
    The Leeds Library by Michael D Beckwith, on Flickr (CC0 1.0).
    

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27. Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    

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29. Applying
    Deep Learning
    Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    Untitled by Marcin Wichary, on Flickr (CC BY 2.0).
    Sharpest tool in the shed by Lachlan Donald, on Flickr (CC BY 2.0).
    

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30. Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    Data Science
    Expertise Computing
    Resources
    High-Quality
    Training Data
    Model Deployment
    Time
    Model
    Integration
    Inferencing Code
    And more…
    Sharpest tool in the shed by Lachlan Donald, on Flickr (CC BY 2.0).
    

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31. ↳ IBM Developer Model Asset Exchange (MAX)
    https://developer.ibm.com/exchanges/models/
    Classify
    Generate
    Recognize
    

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32. Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    Microservice
    Choose deployable model
    Deep Learning asset from the Model Asset Exchange (MAX)
    Deploy
    Swagger specification Inference endpoint Metadata endpoint
    Input preprocessing, model execution, and output post-processing
    Deploy
    model
    Use
    model
    https://developer.ibm.com/exchanges/models/
    

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33. AI Lifecycle
    Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    Deploy &
    Run
    Operate
    & Manage
    Prepare,
    Build &
    Train
    ⇄
    ↳ ⬏
    

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34. ↳ Preparing, Building, and Training AI Models
    Model Asset Exchange (MAX)
    Data Asset Exchange (DAX)
    

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35. ⬏ Deploying and Running AI Models
    ONNX.js
    Model Asset Exchange (MAX)
    

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36. ⇄ Operating and Managing AI Systems
    Fabric for Deep Learning (FfDL)
    Train and deploy deep learning models on Kubernetes using TensorFlow,
    Caffe2, PyTorch, and other frameworks
    Trusted AI
    • AI Fairness 360 Toolkit: Fairness metrics for machine learning models, explanations for
    these metrics, and algorithms to mitigate bias
    • Adversarial Robustness 360 Toolbox: Python library for adversarial attacks and
    defenses for neural networks
    • AI Explainability 360 Toolkit: Interpretability and explainability of data and machine
    learning models
    

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37. What will you
    build with
    deep learning?
    Dynamic Earth - Continental Shelf by NASA Goddard Space Flight Center, on Flickr (CC BY 2.0).
    

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38. Resources: Machine Learning Libraries
    TensorFlow
    https://www.tensorflow.org/
    Train your first neural network: basic classification | TensorFlow
    https://www.tensorflow.org/tutorials/keras/basic_classification
    Keras
    https://keras.io/
    PyTorch
    https://pytorch.org/
    Caffe2
    https://caffe2.ai/
    

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39. Resources: IBM Developer
    IBM Developer
    https://developer.ibm.com/
    IBM Cloud
    https://ibm.biz/BdzXfW
    Center for Open-Source Data & AI Technologies (CODAIT)
    http://codait.org/
    IBM Developer Model Asset Exchange (MAX)
    https://developer.ibm.com/exchanges/models/
    Model Asset Exchange (MAX) Code Patterns
    https://developer.ibm.com/patterns/category/model-asset-exchange/
    magicat
    https://github.com/CODAIT/magicat
    Veremin
    https://veremin.mybluemix.net/
    

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40. Resources: Preparing, Building, and
    Training AI Models
    Project Jupyter
    https://jupyter.org/
    IBM Developer Model Asset Exchange (MAX)
    https://developer.ibm.com/exchanges/models/
    IBM Watson Knowledge Catalog
    https://www.ibm.com/cloud/watson-knowledge-catalog
    IBM Watson Studio
    https://www.ibm.com/cloud/watson-studio
    

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41. Resources: Deploying and Running AI Models
    Data Mining Group (PMML & PFA)
    http://dmg.org/
    ONNX
    https://onnx.ai/
    ONNX.js
    https://github.com/Microsoft/onnxjs
    TensorFlow.js
    https://js.tensorflow.org/
    TensorFlow Lite
    https://www.tensorflow.org/lite
    Core ML
    https://developer.apple.com/machine-learning/
    IBM Watson Machine Learning
    https://www.ibm.com/cloud/machine-learning
    

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42. Resources: Operating and Managing AI Systems
    Fabric for Deep Learning (FfDL)
    https://github.com/IBM/FfDL
    AI Fairness 360 Toolkit
    https://github.com/IBM/AIF360
    Adversarial Robustness 360 Toolbox
    https://github.com/IBM/adversarial-robustness-toolbox
    AI Explainability 360 Toolkit
    https://github.com/IBM/AIX360/
    IBM Watson OpenScale
    https://www.ibm.com/cloud/watson-openscale
    

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43. Thank you.
    Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    Bradley Holt
    Program Manager, Developer Advocacy
    Center for Open-Source Data & AI Technologies
    ↳ (CODAIT)
    —
    @BradleyHolt | @ibmcodait | @IBMDeveloper
    medium.com/codait
    github.com/codait | github.com/IBM
    developer.ibm.com
    

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44. Center for Open-Source Data & AI Technologies (CODAIT) / August 21, 2019 / © 2019 IBM Corporation
    

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