ML - Anomaly Detection via PyCaret
In a nutshell, this concentration helps business professionals get ready for the CDSP exam by teaching them how to put data science knowledge to use in real-world scenarios.
Description for ML - Anomaly Detection via PyCaret
Overview of Anomaly Detection: Understand the principles and significance of anomaly detection in machine learning applications.
Configuration of PyCaret for Anomaly Detection: Configure PyCaret for anomaly detection with minimal coding necessary.
Development and Representation of Algorithms: Develop, illustrate, and evaluate diverse anomaly detection methods to accurately identify outliers.
Hands-On Project-Based Learning: Acquire hands-on experience using PyCaret's tools to construct and evaluate models effectively.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Google Cloud
Duration: 2 hours
Schedule: Hands-on learning
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