Encoding Categorical Data for Machine Learning

Skillsoft issued completion badges are earned based on viewing the percentage required or receiving a passing score when assessment is required. Data processing is essential for effectively managing the various data types encountered in machine learning (ML), setting the stage for advanced analytical tasks. Mastering encoding techniques for categorical variables allows you to convert qualitative data into quantitative formats, facilitating robust model training and insightful analysis. In this course, learn about numerical and categorical data types, how to handle different data types while training ML models, and the best approach for processing them. Next, explore categorical data encoding methods, perform one-hot encoding, and transform categories into numerical forms. Finally, discover how to implement label and ordinal encoding techniques, discretize variables, and train a random forest model. After completing this course, you will be able to encode categorical data for machine learning.