Practical Machine Learning
By Coursera
on Coursera
· Data Science
About This Course
One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.
Instructor
Jeff Leek
Frequently Asked Questions
How much does Practical Machine Learning cost?
Visit the Practical Machine Learning course page for current pricing and available discounts.
Who teaches Practical Machine Learning?
Practical Machine Learning is taught by Jeff Leek, PhD, Johns Hopkins University.
What skill level is Practical Machine Learning for?
This course is designed for all levels learners.