Machine Learning With Polars

Master the Essentials of Modern Machine Learning

Created by: Joram Mutenge
Udemy Instructor

What Will I Learn?

• Explore the fundamentals of an end-to-end machine learning application.
• Carry out basic data cleaning and pre-processing in Python with Polars.
• Build a pipeline to train machine learning models.
• Implement regression, ensemble, and gradient-boosted models
• Deploy a machine learning model using MLFlow.

Requirements

• Very basic Python programming knowledge.
• Familiarity with running code in Jupyter notebooks.

Target audience

• Professionals with tabular data in spreadsheets or databases seeking to make predictions from it.
• Students interested in learning the fundamentals of applied machine learning.
• Students and professionals seeking to learn the implementation of regression, ensemble, and gradient-boosted models.
• Data professionals interested in learning how to deploy a model into production.