About this courseSkip About this course
This Machine Learning with Python course dives into the basics ofMachine LearningusingPython, an approachable and well-known programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each.
You'll look at real-life examples of Machine Learning and how it affects society in ways you may not have guessed!
We'll explore many popular algorithms including Classification, Regression, Clustering, and Dimensional Reduction and popular models such asTrain/Test Split, Root Mean Squared Error and Random Forests.
Mostimportantly, you will transform your theoretical knowledge into practical skill using hands-on labs. Get ready to do more learning than your machine!
What you'll learnSkip What you'll learn
- Supervised vs Unsupervised Machine Learning
- How Statistical Modeling relates to Machine Learning, andhow to do a comparison of each.
- Different waysmachinelearning affects society
Module 1 - Introduction to Machine Learning
Applications of Machine Learning
Supervised vs Unsupervised Learning
Python libraries suitable for Machine Learning
Module 2 - Regression
Model evaluation methods
Module 3 - Classification
Support Vector Machines
Module 4 - Unsupervised Learning
Module 5 - Recommender Systems
Content-based recommender systems
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Who can take this course?
Unfortunately, learners from one or more of the following countries or regions will not be able to register for this course: Iran, Cuba and the Crimea region of Ukraine. While edX has sought licenses from the U.S. Office of Foreign Assets Control (OFAC) to offer our courses to learners in these countries and regions, the licenses we have received are not broad enough to allow us to offer this course in all locations. EdX truly regrets that U.S. sanctions prevent us from offering all of our courses to everyone, no matter where they live.