Feature importance and model interpretation in Python free download

Feature importance makes us better understand the information behind data and allows us to reduce the dimensionality of our problem . A common dimensionality reduction technique based on feature importance is the Recursive Feature Elimination . Model interpretation helps us to correctly analyze and interpret the results of a model . How to use SHAP technique to calculate feature importance of every model. How to apply RFE with and without cross-validation. A common approach for calculating model. What you’ll learn in Feature importance and model interpretation in Python using Python programming language. The practical course is based on a practical use of the language and a common approach to calculating model .

What you’ll learn in Feature importance and design analysis in Python

  1. How to calculate function value according to a number of models
  2. Exactly how to use SHAP strategy to determine feature significance of every model
  3. Recursive Attribute Elimination
  4. Just how to use RFE with and also without cross-validation


In this functional course, we are going to concentrate on function value as well as version analysis in monitored artificial intelligence using Python shows language.

Attribute value makes us better recognize the details behind information as well as enables us to reduce the dimensionality of our issue thinking about only the pertinent information, throwing out all the pointless variables. An usual dimensionality decrease strategy based upon function value is the Recursive Function Elimination.

Version interpretation aids us to correctly analyze as well as analyze the outcomes of a version. A typical method for determining model interpretation is the SHAP technique.

With this training course, you are mosting likely to find out:

All the lessons of this training course begin with a short intro and also end with a practical example in Python programs language and also its effective scikit-learn collection. The atmosphere that will certainly be made use of is Jupyter, which is a standard in the information science market. All the Jupyter note pads are downloadable.

This program becomes part of my Monitored Machine Learning in Python on-line program, so you’ll locate some lessons that are currently included in the larger course.

Who this course is for:

  • Python developers
  • Data Scientists
  • Computer engineers
  • Researchers
  • Students
File Name :Feature importance and model interpretation in Python free download
Content Source:udemy
Genre / Category:Development
File Size :3.00 gb
Publisher :Gianluca Malato
Updated and Published:08 Aug,2022

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File name: Feature-importance-and-model-interpretation-in-Python.rar
File Size:3.00 gb
Course duration:5 hours
Instructor Name:Gianluca Malato
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