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Machine Learning for Domain Experts
- 1. Machine Learning for Domain Experts Alican Noyan ipsumio.com
- 2. Introduction Data – Learning Algorithm – Model Code Overfi?ng/Underfi?ng ML systems How to approach ML projects Understanding Application
- 4. 4 Symbolic AI Machine Learning Ar4ficial Intelligence
- 5. Symbolic AI Machine Learning Supervised Unsupervised Symbolic AI Machine Learning Supervised Unsupervised Artificial Intelligence • Neural Network • Linear Regression • Random Forest Deep Learning 5 Regression Classification Particle size measurement Cell A or Cell B
- 6. Tools
- 8. Problem definiOon Deployment Data collection & Labeling Model development High level objective Data science problem Big data Good data Learning algorithm Model Hand the model to domain experts
- 9. Introduction Data – Learning Algorithm – Model Code Overfitting/Underfitting ML systems How to approach ML projects
- 10. Data Model 2.5 x Chocolate Consumption - 5 = Number of Nobel Laureates Learning Algorithm
- 12. Universal properties Particular properties Book = Book-ness + Par4culars Data = Signal + Noise
- 13. 13 -1 0 1 3 4 -3 -1 1 5 7 What is the relationship? Relationship, Pattern, Function, Model, Hypothesis 2 ? Given 2, predict green
- 14. Machine Learning y = 2x - 1 14 Generalization Training set Test set
- 15. Introduction Data – Learning Algorithm – Model Code Overfitting/Underfitting ML systems How to approach ML projects
- 17. Introduction Data – Learning Algorithm – Model Code Overfitting/Underfitting ML systems How to approach ML projects
- 18. Data = Signal + Noise Fit Overfitting Underfitting
- 19. x3 x3 x10 x Overfi?ng vs. Underfi?ng due to model capacity
- 20. Overfitting vs. Underfitting due to model capacity More data?
- 21. x3 x10 x Overfitting vs. Underfitting due to model capacity Extrapolation?
- 22. Data = Signal + Noise Fit Overfi[ng Underfitting Let’s get real
- 23. x3 x3 x2 x x3 fit Underfi?ng in pracOce Population Sample Data = Signal + Noise
- 25. x3 x2 x x3 fit Underfitting in practice More data?
- 26. x3 x2 x x3 fit Overfitting in practice Data = Signal + Non-random noise + Random noise
- 29. Overfitting in practice More data?
- 30. Data = Signal + Noise
- 31. Introduction Data – Learning Algorithm – Model Code Overfi?ng/Underfi?ng ML systems How to approach ML projects
- 35. Introduction Data – Learning Algorithm – Model Code Overfitting/Underfitting ML systems How to approach ML projects
- 36. 36 How to find an ML project Image processing • Classify images • Localize objects inside images • Count objects in video • Measure x Feature 1 Feature 2 Target Example 1 Example 2 Example 3 Example 4 … Sensor Raw data Measurement Non-ML Model Optimization
- 37. 37 Do you really need machine learning?
- 38. Are you solving the correct problem? Do you have the signal inside your dataset? Does your sample represent the population? Do you have non-random noise in your dataset? Surpass a physician’s ability to predict disease Predict normal heart function Body temperature
- 39. 39 Class activation maps Cardiomegaly prediction https://medium.com/@jrzech/what-are-radiological-deep-learning-models-actually-learning-f97a546c5b98
- 40. Positive/Negative source "We show that similar results can be obtained using X-ray images that do not contain most of the lungs." https://arxiv.org/abs/2004.12823 40 Negative data source COVID-19 data source A, B, C … X, Y, Z … 415 studies 0 clinically useful
- 41. Explicitly state the limitations 41
- 42. Sample vs. Population May-Grünwald-Giemsa stain Papanicolaou stain https://www.springer.com/gp/book/9783030107215 42
- 43. Sample vs. Population https://www.springer.com/gp/book/9783030107215 https://jsstd.org/cytodiagnosis-in-dermatology/ 43
- 45. Train/Test information leakage Patient 1 Patient 2 Patient 3 Patient 4 Patient 5 PaOent 6 Images Train Test 45
- 46. External testing Hospital X Dr. A ProspecOve Dr. B Dr. C Dr. D Hospital Z Country K Hospital X Hospital X Hospital Y Country K Country K Country K Country L Train/Test Dr. A 46
- 47. Training Dr. A Dr. B Dr. C Dr. D Hospital Z Hospital X Hospital X Hospital Y Country K Country K Country K Country L 47