Machine Learning - Anomaly Detection via PyCaret

Offered By
Coursera Project Network
In this Guided Project, you will:

Anomaly Detection Models

Clock2 hours
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this 2 hour long project-based course you will learn how to perform anomaly detection, its importance in machine learning, set up PyCaret anomaly detection, create, visualize & compare anomaly detection algorithms all this with just a few lines of code.

Skills you will develop

  • Anomaly Detection
  • Machine Learning
  • Data Visualization (DataViz)
  • PyCaret

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. 1. Import data and exploratory anomalies detection analysis

  2. 2. Setup PyCaret environment for anomaly detection

  3. 3. Select and create models

  4. 4. Compare anomalies in models

  5. 5. visualize, interpret decision, and save the model

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.