how_to_start_ml.md

Getting Started in Machine Learning

Make sure you are comfortable with the core prerequisites.

See: prerequisites.md.

---

Recommended First Resource

Start with Andrew Ng's Machine Learning Specialization

• one of the best introductions to machine learning
• still especially relevant today
• accessible yet rigorous

---

Key Concepts to Know

You ought to become familiar with the following terms. These are part of the basic vocabulary of machine learning:

• Training, Validation, and Testing datasets
• Supervised vs. Unsupervised learning
• Overfitting and Underfitting
• Cross-validation, k-fold cross-validation, stratified sampling, data leakage
• Performance metrics: Accuracy, F1 score, Precision vs. Recall, Weighted metrics
• Bias-variance tradeoff

---

Next steps:

Build your theoretical understanding reading books.

Start exercising using Dive into Deep Learning:

• Chapter 1 - Introduction: https://d2l.ai/chapter_introduction/index.html
• Chapter 2 - Preliminaries: https://d2l.ai/chapter_preliminaries/index.html
• Chapter 3.1 - Linear Regression: https://d2l.ai/chapter_linear-regression/linear-regression.html