Machine Learning Basics: Pick the Problem Type First

When you're starting with machine learning, the most useful first step isn't picking an algorithm, it's naming the problem type.

• Supervised learning: you have labeled examples and want predictions.
• Unsupervised learning: you have data and want to find structure.
• Reinforcement learning: an agent learns from trial, error, and reward.

Once you know the type, the algorithm shortlist basically writes itself, and a lot of beginner confusion disappears.

Full beginner-friendly breakdown here: https://www.learnhowtoscience.com/machine-learning-basics/