The first challenge in the machine learning life cycle is understanding the problem or opportunity; the next is acquiring, understanding, and preparing data for the modeling phase. This second step is estimated take more than 50% of the time allotted for a machine learning project. This course addresses how to translate the problem statement, identify data sources, explore data for relationships and patterns, identify the starting inputs for the model, prepare data, and validate it for the model fitting process.
There are no prerequisites for this course.
Join our public courses in our Switzerland facilities. Private class trainings will be organized at the location of your preference, according to your schedule.