Machine Learning:
Analytics in which computers “learn” from data to produce models or rules that apply to those data and to other similar data. Predictive modeling techniques such as neural nets, classification and regression trees (decision trees), naive Bayes, k-nearest neighbor, and support vector machines are generally included. One characteristic of these techniques is that the form of the resulting model is flexible, and adapts to the data. Statistical modeling methods that have highly structured model forms, such as linear regression, logistic regression and discriminant analysis are generally not considered part of machine learning. Unsupervised learning methods such as association rules and clustering are also considered part of machine learning.
Browse Other Glossary Entries
Test Yourself
Planning on taking an introductory statistics course, but not sure if you need to start at the beginning? Review the course description for each of our introductory statistics courses and estimate which best matches your level, then take the self test for that course. If you get all or almost all the questions correct, move on and take the next test.
Data Analytics
Considering becoming adata scientist, customer analyst or our data science certificate program?
Analytics Quiz
Advanced Statistics Quiz
Statistics Quiz
Courses
Find the right course for you
Contact Us
We'd love to answer your questions
Our mentors and academic advisors are standing by to help guide you towards the courses or program that makes the most sense for you and your goals.
300 W Main St STE 301, Charlottesville, VA 22903
(434) 973-7673
ourcourses@statistics.com