ML Interview Notes
Notes

Machine Learning

Core Machine Learning concepts, algorithms, model evaluation, and best practices.

These notes are being written. Each topic below will become its own page. Contributions are welcome — every page is a Markdown file in the repository.

Planned topics

Topic Level Tags
Types of ML beginner supervised, unsupervised, reinforcement learning
ML Algorithms intermediate regression, classification, clustering
Model Evaluation intermediate cross-validation, metrics, confusion matrix
Feature Engineering intermediate feature selection, scaling, normalization
Hyperparameter Tuning advanced grid search, random search, bayesian optimization
Ethics in ML intermediate bias, fairness, explainable AI