PyCaret: Anatomy of Classification

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Coursera Project Network
In this Guided Project, you will:

All the steps from environment setup, model performance, multi model stacking to visualizations

Clock2 hours 10 minutes
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this 2 hour 10 mins long project-based course, you will learn how to set up PyCaret Environment and become familiar with the variety of data preparing tasks done during setup, be able to create, see and compare performance of several models, learn how to tune your model without doing an exhaustive search, create impressive visuals of models, feature importance and much more. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

Auto MLData ScienceMachine Learningclassification

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. Import Data, Initial dataset check and setup Pycaret(install and set up environment)

  2. Compare model performance

  3. Create best performing models

  4. Hyper Parameter tuning the models

  5. Stacking, Blending & Ensemble multiple models

  6. Visualize performance

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

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Frequently Asked Questions

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