Description:

Scikit-Learn is one of the major libraries for machine learning in Python. This series comprises four workshops designed to give you a map of Scikit-Learn’s different functionalities and place you on firm ground to start using it for your machine-learning projects. 

Part 2 - Supervised Learning – Regression 
Regression analysis is a powerful tool for uncovering the associations between features of your data (known as independent variables) and dependent variables (usually denoted by Y). In this workshop, you will learn to identify ML tasks suited for regression analysis, appropriately process independent variables, train and evaluate models, and generate predictions. We will also discuss some common pitfalls and assumptions of the chosen modeling techniques. 

Prerequisites: Basic familiarity with Python is required. Familiarity with NumPy is highly recommended. No previous machine learning or statistics experience is necessary, but it will be helpful.