The following set of tutorials is loosely based on the source code I prepared for my book "Machine learning with Swift: Artificial Intelligence for iOS".
This is still work-in-progress project (and maybe always will be), so the pages that are more or less ready for reading are marked with bold font.
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Section I: ML Intro
- Chapter 1. Getting started with Machine Learning
- Data science toolbox
- Chapter 2. Decision Tree Learning
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Section II: Statistical Learning
- Chapter 3. k-Neares Neighbor Classifier
- Chapter 4. Clustering
- Chapter 5. Rule Learning
- Chapter 6. Linear Regression
- Chapter 7. Logistic Regression
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Section III: Deep Learning
- Chapter 8. Neural Networks
- Chapter 9. Convolutional Neural Networks and Computer Vision
- Chapter 10. Word Embeddings and Natural Language Processing
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Section IV: ML in Production
- Chapter 11. Machine Learning Libraries
- Chapter 12. Hardware Accelerartion
- Chapter 13. Optimizing Neural Networks for Mobile Devices
- Chapter 14. Best Practices
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Supplementary Materials:
Contributors: