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 3 - Supervised Learning – Classification 
Classification is the problem of identifying which class or category (label) an observation (features) belongs to within a pre-defined set of categories. In this workshop, you will learn to identify classification problems, prepare the features and label data for modeling, 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.