Recommendation Engines perform a variety of tasks, but the most important one is to find products that are most relevant to the user. Follow along with this intensive Recommendation Systems in Python training course to get a firm grasp on this essential Machine Learning component.

Course Info

Requirements:

• No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided.

Highlights:

• Learn about Movielens - a famous dataset with movie ratings
• Use Pandas to read and play around with the data
• Learn how to use Scipy and Numpy
• Introduction to Latent Factor Methods
• Introduction to Memory-based Approaches
• Design & implement a Recommendation System in Python

Target Audience:

• Analytics professionals, modelers, big data professionals who haven’t had exposure to machine learning
• Engineers who want to understand or learn machine learning and apply it to problems they are solving
• Product managers who want to have intelligent conversations with data scientists and engineers about machine learning
• Tech executives and investors who are interested in big data, machine learning or natural language processing
• MBA graduates or business professionals who are looking to move to a heavily quantitative role