Anomaly Detection: Machine Learning, Deep Learning, AutoML

Recent UpdatesJuly 2025: Added a video lecture on hybrid approach (combining clustering and non clustering algorithms to identify anomalies)Feb 2025: Added a video lecture on "Explainable AI". This is an emerging and a fascinating area to understand the drivers of outcomes. Jan 2025: Added anomaly detection algorithms (Auto Encoders, Boltzmann Machines, Adversarial Networks) using deep learningNov 2025: We all want to know what goes on inside a library.

We have explained isolation forest algorithm by taking few data points and identifying anomaly point through manual calculation. A unique approach to explain an algorithm. July 2025: AutoML is the new evolution in IT and ML industry.

AutoML is about deploying ML without writing any code. Anomaly Detection Using PowerBI has been added. June 2025: A new video lecture on balancing the imbalanced dataset has been added.

May 2025: A new video lecture on PyOD: A comparison of 10 algorithms has been addedCourse DescriptionAn anomaly is a data point that doesn't fit or gel with other data points. Detecting this anomaly point or a set of anomaly points in a process area can be highly beneficial as it can point to potential issues affecting the organization. In fact, anomaly detection has been the most widely adopted area with in the artificial intelligence - machine learning space in the world of business.