Apply Supervised and Unsupervised Learning Algorithms using Scikit-Learn to Solve Real-World Problems

Learning Objectives:

At the end of this topic, you must be able to:
1. Analyse a real-world problem and classify it as suitable for a supervised or unsupervised approach.
2. Select and implement appropriate supervised algorithms using scikit-learn for classification and regression tasks.
3. Select and implement appropriate unsupervised algorithms using scikit-learn for clustering and dimensionality reduction tasks.
4. Load and prepare a dataset for modelling using standard Python workflows.
5. Produce a trained model and interpret its output in relation to the original problem.
6. Document and version-control machine learning code in accordance with industry practice.