Detecting Data Anomalies using Deep Learning Techniques with TensorFlow 2.4

This course will teach you how to create deep-learning algorithms for detecting and mitigating anomalies in data such as time series.

In this course, Detecting Data Anomalies using Deep Learning Techniques with TensorFlow 2.4, you’ll learn to spot specific patterns in large datasets that can be labelled as anomalies. First, you’ll explore how to precisely define anomalies in data. Next, you’ll discover detection algorithms. Finally, you’ll learn how to mitigate anomalous data. When you’re finished with this course, you’ll have the skills and knowledge of creating machine learning algorithms needed for dealing with various anomalies in data.

• Course Overview 2mins
• Introduction 16mins
• Exploratory Data Analysis 12mins
• Definition and Anomaly Types 13mins
• Detection Algorithms 39mins
• Mitigation Techniques 8mins