Applied Unsupervised Learning with R

Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions.

This course begins with the most important and commonly used method for unsupervised learning – clustering – and explains the three main clustering algorithms – k-means, divisive, and agglomerative. Following this, you’ll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You’ll be introduced to these methods using code written in R, with further instructions on how to work with, edit, and improve R code. To help you gain a practical understanding, the course also features useful tips on applying these methods to real business problems, including market segmentation and fraud detection. By working through interesting activities, you’ll explore data encoders and latent variable models.

By the end of this course, you will have a better understanding of different anomaly detection methods, such as outlier detection, Mahalanobis distances, and contextual and collective anomaly detection.

About the Author

• Alok Malik is a data scientist based in India. He has previously worked on creating and deploying unsupervised learning solutions in fields such as finance, cryptocurrency trading, logistics, and natural language processing. He has a bachelor’s degree in technology from the Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, where he studied electronics and communication engineering.Bradford Tuckfield has designed and implemented data science solutions for firms in a variety of industries. He studied math for his bachelor’s degree and economics for his Ph.D. He has written for scholarly journals and the popular press, on topics including linear algebra, psychology, and public policy.

• Bert Gollnick is a Diploma in Aerospace Engineering and has pursued MSc in Economics.

  He is also a Data Scientist and has 10 years experience in R. He is also an online trainer for Data Science and Machine Learning.

Rating Distribution

• 1 stars: 0 votes
• 2 stars: 0 votes
• 3 stars: 0 votes
• 4 stars: 3 votes
• 5 stars: 4 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!