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1
- Introduction
2
- Learning Objectives
3
- What is classification?
4
- Binary classification
5
- The logistic function
6
- Classification threshold
7
- Exercise: Evaluate classification models
8
- Other performance metrics
9
- Classification report review
10
- Knowledge check
11
- Summary and conclusion
Description:
Explore the fundamentals of classification in machine learning through this comprehensive 1.5-hour video tutorial. Discover when to use classification and how to train and evaluate classification models using the Scikit-Learn framework. Delve into topics such as binary classification, the logistic function, and classification thresholds. Participate in hands-on exercises to evaluate classification models and gain insights into various performance metrics. Review classification reports and test your knowledge with a quiz. Presented by Microsoft Cloud Advocate Ruth Yakubu and Developer Advocate Lead David Smith, this tutorial is part of the Learn Live series and includes links to additional resources for further learning on Microsoft Learn.

Train and Evaluate Classification Models

Microsoft
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