This solution will transform the user input data by running machine learning related feature engineering operations as specified by the user. It can process tabular data which can have categorical and numerical values. The solution provides the most common feature engineering techniques including but not limited to check for inter-feature interaction, apply polynomial and trigonometric functions and can also remove rare levels.

This solution saves a significant amount of time spent over developing and running different feature engineering operations on the data. This improves data scientists/engineers productivity and allows them to focus on more value added parts in the data science experiments.

PACE - ML is Mphasis Framework and Methodology for end-to-end machine learning development and deployment. PACE-ML enables organizations to improve the quality & reliability of the machine learning solutions in production and helps automate, scale, and monitor them. Need customized Machine Learning and Deep Learning solutions? Get in touch!