Complete Outlier Detection Algorithms A-Z: In Data Science

Welcome to the course Complete Outlier Detection Algorithms A–Z: In Data Science .

This is the most comprehensive, yet straight–forward, course for the outlier detection on UDEMY!

Are you Data Scientist or Data Analyst or Financial Analyst or maybe you are interested in anomaly detection or fraud detection? The course is designed to teach you the various techniques which can be used to identify and recognize outliers in any set of data.

The process of identifying outliers has many names in Data Science and Machine learning such as outlier modeling, novelty detection, or anomaly detection. Outlier detection algorithms are useful in areas such as Machine Learning, Deep Learning, Data Science, Pattern Recognition, Data Analysis, and Statistics.

I will present to you very popular algorithms used in the industry as well as advanced methods developed in recent years, coming from Data Science. You will learn algorithms for detection outliers in Univariate space, in Low–dimensional space and also learn the innovative algorithms for detection outliers in High–dimensional space.

I am convinced that only those who are familiar with the details of the methodology and know all the stages of the calculation, can understand it in depth. Anyone who interested in programming, I developed all algorithms in PYTHON, so you can download and run them.