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You Can Do Deep Learning!

You Can Do Deep Learning!

It’s 2018, and you don’t need a PhD to do deep learning. This talk will empower you to build your first deep learning project using Python and open-source tools. In other domains, like web development, we leverage frameworks that give us high-level abstractions to work with, and I will show you that deep learning doesn’t have to be different.


William Horton

July 28, 2018

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  1. You Can Do Deep Learning! By William Horton

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  3. Image Classifier cat? dog?

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  5. Other applications

  6. Who am I? • Backend Engineer, Data Team at Compass

    • Python • Deep Learning
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  8. Let’s dive in!

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  10. Deep Learning

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  14. $ gem install rails $ rails new blog $ cd

    blog $ bin/rails server $ pip install Django $ django-admin startproject blog $ cd blog $ python manage.py runserver
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  17. Magic!

  18. Deep Learning

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  20. Common roadblocks What about the math? Having to learn everything

    about everything before you even let yourself start Thinking you can’t do this because you don’t have a PhD
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  22. the fast.ai formula:

  23. Math is important Theory is important But why not start

    with the knowledge and skills that you have?
  24. https://cloud.google.com/blog/big-data/2016/08/how-a-japanese-cucumber-farmer-is- using-deep-learning-and-tensorflow

  25. Use what you know!

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  28. You know how to translate ideas into working code.

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  30. You know how to read the documentation and source of

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  32. You’ve probably spent hours of your life debugging.

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  34. Putting it together

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  36. Kaggle Kernels

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  38. fast.ai library

  39. Communities fast.ai forums Pytorch forums Kaggle discussion threads AI Saturdays

    Medium Twitter
  40. http://tools.google.com/seedbank/

  41. What can I do?

  42. Near term questions What happens if I train for longer?

    What happens if I change the learning rate? Can I apply this to another dataset? Can I use a different architecture? What is training loss? What is validation loss?
  43. Understand, implement, and explain https://medium.com/@radekosmulski/do-smoother-ar eas-of-the-error-surface-lead-to-better-generalization- b5f93b9edf5b http://teleported.in/posts/cyclic-learning-rate/

  44. https://medium.com/@hortonhearsafoo/adding-a-cutting-edge-deep-learning-train ing-technique-to-the-fast-ai-library-2cd1dba90a49

  45. Win an Emmy?

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  48. Tackle your business problems

  49. Take on the giants https://www.theverge.com/2018/5/7/17316010/fast-ai-speed-test-stanford-dawnbe nch-google-intel

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  52. Now get started! (And let me know: @hortonhearsafoo)

  53. Image Credits Terminator: https://www.sideshowtoy.com/assets/products/300157-terminator-t-800-endoskeleton/lg/terminator-2-terminator-t-800-endoskeleton-m aquette-sideshow-300157-17.jpg Dog: https://i.ytimg.com/vi/SfLV8hD7zX4/maxresdefault.jpg Cat: https://upload.wikimedia.org/wikipedia/commons/thumb/3/3a/Cat03.jpg/1200px-Cat03.jpg ImageNet

    graph: https://www.economist.com/special-report/2016/06/25/from-not-working-to-neural-networking Google Translate: https://translate.google.com/ AlphaGo: https://deepmind.com/research/alphago/ Compass: https://www.compass.com/ Tensorflow: screenshotted from https://www.tensorflow.org/ Coursera: from https://www.facebook.com/Coursera/ Khan Academy: https://cdn.kastatic.org/images/khan-logo-dark-background.png Kaggle: https://en.wikipedia.org/wiki/Kaggle Udacity: https://d20vrrgs8k4bvw.cloudfront.net/images/open-graph/udacity.png Roadblock: https://thesandwichedman.files.wordpress.com/2017/03/roadblock.jpg?w=519 You Shall Not Pass: https://coldcallcoach.net/donts-grappling-gatekeeper/ django: https://en.wikipedia.org/wiki/Django_(web_framework) Rails: screenshotted from https://www.youtube.com/watch?v=Gzj723LkRJY DHH: http://david.heinemeierhansson.com/images/me.jpg
  54. You’re on rails: screenshotted from https://guides.rubyonrails.org/getting_started.html Magic: https://recruitingtools.com/wp-content/uploads/sites/2/2017/07/magic-wand.jpg fastai: http://www.fast.ai/

    fastai video: https://www.youtube.com/watch?v=Th_ckFbc6bI fastai formula: screenshotted from http://course.fast.ai/ python: https://www.python.org/ jira ticket: http://www.taigeair.com/JIRA-Ticket mockup: https://wireframesketcher.com/sample-mockups.html keras documentation: https://keras.io/getting-started/functional-api-guide/ pytorch github: https://github.com/pytorch/pytorch stack trace: http://i45.tinypic.com/nzm99h.jpg stackoverflow: https://stackoverflow.com/ gpu: https://www.notebookcheck.net/fileadmin/_processed_/d/3/csm_GeForce_GTX_1080ti_3qtr_top_left__f25b948c6c.jpg data: http://metaltechalley.com/wp-content/uploads/2017/09/data.jpg jupyter: http://jupyter.org/assets/try/jupyter.png tensorflow: https://upload.wikimedia.org/wikipedia/commons/thumb/1/11/TensorFlowLogo.svg/2000px-TensorFlowLogo.svg.png keras: https://keras.io/ scikit-learn: https://twitter.com/scikit_learn pytorch: https://pytorch.org/ emmy nominations: http://www.emmys.com/awards/nominees-winners/2018/outstanding-creative-achievement-in-interactive-media-within-a-scripted-progr am not hotdog app: http://www.bgr.in/news/the-ridiculous-not-hotdog-app-is-real-and-here-are-6-other-apps-if-you-love-it/ not hotdog linkedin post: https://www.linkedin.com/feed/update/urn:li:activity:6423300978275082240/ dawnbench: https://dawn.cs.stanford.edu/benchmark/