Machine learning from a software engineer's perspective - Marijn van …

About me @marijnvanzelst Marijn van Zelst • Software engineer at Luminis Amsterdam 3. Goal: • Practical knowledge about machine learning • What kind of problems it can solve • Do your own experiment 4. Why is machine learning interesting for Software Developers? • New opportunities • Builds on existing knowledge • Open-source communities and libraries 5. Tensorflow • Developed by Google • Open-source • Has api's for most major programming languages • High level api 6. Machine learning Learn from examples 7. Handwritten digit classification MNIST dataset 8. What is the difference between a 2 and a 3? 9. Neural networks Image recognition Speech recognition Natural language recognition Churn prediction Fraud detection Anomaly detection 10. Learning algorithm • While not done • pick a training example (input data, class) • run it through the neural network which produces a prediction • modify the weights in the neural network so that the prediction is closer to the actual class 14. Agile approach to machine learning • Theory takes a lot of time to explain and learn • Using high level api's you can do experiments without knowing all the mathematical details • When you have your first results and want to improve • Learn more • Ask for expert help 15. Using a high level api • Which features do I use? Neural nets intuition • Input: • Features (coordinates in feature space) • Output: • A predicted class at every coordinate in the feature space white black black y x 24.