Association Rule Learning: Background Association Rule Learning (also called Market Basket Analysis) is a practical and highly interpertable starting place for implementing the first recommendation algorithm for your business. Association rules, or strong relationships between variables in a dataset, can be mined from historical data using an appropriate algorithm. Those rules can then be leveraged to effectively predict future user behavior. Association rules are commonly applied to assist with marketing decisions such as selecting users for a specific ad campaign, recommending personalized services, or smart product up-selling at checkout.

Chelsea French

Experienced Machine Learning Engineer with a master’s degree in Neuroscience and a strong background in Python, SQL, and data analytics.

Senior Data Scientist

San Diego, California