Detecting Data Anomalies using Deep Learning Techniques with TensorFlow 2.4

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Free Online Course: Detecting Data Anomalies using Deep Learning Techniques with TensorFlow 2.4 provided by Pluralsight is a comprehensive online course, which lasts for 1-2 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from Pluralsight. Detecting Data Anomalies using Deep Learning Techniques with TensorFlow 2.4 is taught by Andrei Pruteanu.

Overview
  • 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.