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  1. 1. Expert systems, transfer learning and its impact on your next big project Galvin Widjaja Lauretta.io
  2. 2. Galvin Widjaja @galvinw | github.com/galvinw Graduated: Singapore Management University is Quant Finance Work: Management Consulting → Business Process Management → Monte Carlo Systems → Process Strategy → IT Strategy → Data Science Transition: MIT Visiting Scholar → CFO at Pinchfavor Inc. (New York) Current: Founder - Lauretta.io (ML Pipeline and Human Automation) CEO - Bttrigitical AI (Petrochem AI Solutions) Management Director - Es Teler 77 Singapore Indonesia Developer Summit 2017 About Me
  3. 3. Agenda ● What is transfer learning, what are expert systems and are robots going to take over the world ● Build your own image recognition in 20 minutes ● The Limitations for Small timers and why the limits are being lifted Indonesia Developer Summit 2017
  4. 4. Indonesia Developer Summit 2017 Transfer Learning A field focused on storing knowledge gained while solving one problem and applying it to a different but related problem
  5. 5. Indonesia Developer Summit 2017
  6. 6. Indonesia Developer Summit 2017
  7. 7. Indonesia Developer Summit 2017 Expert Systems A computer system that emulates the decision-making ability of a human expert
  8. 8. Indonesia Developer Summit 2017 Expert Systems
  9. 9. Are machines going to take over the world? Well, obviously they are... Indonesia Developer Summit 2017 So you better be on their good side when it happens
  10. 10. Build your own image recognition in 20 minutes Indonesia Developer Summit 2017
  11. 11. Indonesia Developer Summit 2017All code at : https://github.com/galvinw/deeplearning.ai thanks to Deeplearning.ai Initialize Python with Keras, Tensorflow and Numpy. Essentially this allows you to do any image recognition task
  12. 12. Indonesia Developer Summit 2017All code at : https://github.com/galvinw/deeplearning.ai thanks to Deeplearning.ai Define a model: Extract Features Where are the: 1. Vertical lines 2. Horizonal lines 3. Circles 4. Big circles 5. Clear.. circles? 6. ...squiggles
  13. 13. Indonesia Developer Summit 2017All code at : https://github.com/galvinw/deeplearning.ai thanks to Deeplearning.ai Define a model: Analyse with DNN Each feature becomes a set of arbitrary data points that is stored in a large set of neurons
  14. 14. Indonesia Developer Summit 2017All code at : https://github.com/galvinw/deeplearning.ai thanks to Deeplearning.ai Looks super hard… but only 9 lines of code Thanks to Keras (High level framework) and Tensorflow (Handles all the optimization and complicatedness) This line says, use 32 types of features.
  15. 15. Optional: Recognise the object first Indonesia Developer Summit 2017 This is hard (we won’t touch it)
  16. 16. Indonesia Developer Summit 2017All code at : https://github.com/galvinw/deeplearning.ai thanks to Deeplearning.ai Initialize Python with Keras, Tensorflow and Numpy. Essentially this allows you to do any image recognition task
  17. 17. Indonesia Developer Summit 2017All code at : https://github.com/galvinw/deeplearning.ai thanks to Deeplearning.ai Identify Objects Basically you draw boxes all over an image and check if there’s something interesting in one of them
  18. 18. Indonesia Developer Summit 2017All code at : https://github.com/galvinw/deeplearning.ai thanks to Deeplearning.ai Suppress bad predictions Called “intersection over union (IoU)” This merges good bounding boxes
  19. 19. Indonesia Developer Summit 2017All code at : https://github.com/galvinw/deeplearning.ai thanks to Deeplearning.ai Suppress bad predictions First, you choose boxes that don’t have high likelihood of having a feature and discard it, then you merge the rest of the boxes using “intersection over union (IoU)”. - This merges good bounding boxes
  20. 20. Indonesia Developer Summit 2017All code at : https://github.com/galvinw/deeplearning.ai thanks to Deeplearning.ai Do Image Recognition of each box First, you choose boxes that don’t have high likelihood of having a feature and discard it, then you merge the rest of the boxes using “intersection over union (IoU)”. - This merges good bounding boxes
  21. 21. The Limitations for Small timers and why the limits are being lifted Indonesia Developer Summit 2017
  22. 22. Indonesia Developer Summit 2017 The Venn diagram of our problems No Data
  23. 23. Complicated Indonesia Developer Summit 2017 Not with these frameworks Tensorboard and development is available instantly with the use of tensorflow
  24. 24. Lacking Data? Indonesia Developer Summit 2017 Transfer learning is fully proven to work well on all image recognition. Most frameworks are trained on ImageNet given you a baseline of 1 million images Also new techniques seem to be able to use up to 1% as much data as previously required
  25. 25. Processing Power Indonesia Developer Summit 2017 With smaller data requirements, processing needs are decreasing. But even so, Google ML provides fairly cheap GPU usage with many student concessions
  26. 26. Conclusion The robots are coming to be our overlords. Get a job as one of their technicians now. (No seriously, get ready for this) … also we might be recruiting Indonesia Developer Summit 2017

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