References¶
Articles¶
- Rules of Machine Learning: Best Practices for ML Engineering
- Neural Networks, Types, and Functional Programming
- MLOps: Continuous delivery and automation pipelines in machine learning
Papers¶
- Statistical Learning Theory: Models, Concepts, and Results
- Hidden Technical Debt in Machine Learning Systems
Books¶
- Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares
- An Introduction to Statistical Learning – with Applications in R
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction
- Pattern Recognition and Machine Learning
- Forecasting: Principles and Practice
Courses¶
- Machine Learning Coursera – Andrew Ng
- Machine Learning edX – John Paisley
- A Course in Machine Learning – Hal Daumé III