Python is a popular programming language for building machine learning models. Facilitating the process, is the powerful library Scikit-Learn, which contains nearly all of the most common machine learning algorithms of the day. Scikit-Learn provides an easy-to-use API that allows for training, validation, and prediction in just a few lines of code.

In this webinar, we’ll take a tour of the available tools provided by Scikit-Learn, then uncover the distinction between an estimator and a function, which is key to understanding how to use the API. We’ll dig deep into the estimator object in Scikit-Learn, which drives the learning and behaves similarly for nearly all models.

Additionally, we will cover the data preprocessing that Scikit-Learn necessitates before training. And finally, we’ll go in-depth with examples from data ingestion to model fitting, validation, and prediction.