Course Preprocessing for Machine Learning in Python
In this course you’ll learn how to get your cleaned data ready for modeling.
This online course about Preprocessing for Machine Learning in Python covers a key part of what a future data analyst would require.
This course covers the basics of how and when to perform data preprocessing. This essential step in any machine learning project is when you get your data ready for modeling. Between importing and cleaning your data and fitting your machine learning model is when preprocessing comes into play. You’ll learn how to standardize your data so that it’s in the right form for your model, create new features to best leverage the information in your dataset, and select the best features to improve your model fit. Finally, you’ll have some practice preprocessing by getting a dataset on UFO sightings ready for modeling.
Enroll now in this Preprocessing for Machine Learning in Python course, and don’t miss the opportunity of learning with the best, as Sarah Guido is. With 62 enriching exercises, 20 videos, and an estimated time of 4 hours to successfully end up the course, you will become one of the best.
Senior Data Scientist at InVision
Sarah is a Senior Data Scientist at InVision where she studies user collaboration through data. She is an accomplished conference speaker, conference track chair, and O’Reilly Media author, and is passionate about Python and machine learning. Sarah attended graduate school at the University of Michigan’s School of Information.