[Feature Request]: Machine Learning Model Evaluation and Selection

[navyabijoy]

Is there an existing issue for this?

• I have searched the existing issues

Feature Description

The notebook will contain the following steps:

• split datasets into training, cross validation, and test sets
• evaluate regression and classification models
• add polynomial features to improve the performance of a linear regression model
• compare several neural network architectures

Use Case

Quantifying a learning algorithm's performance and comparing different models are some of the common tasks when applying machine learning to real world applications, this notebook will act as a perfect guide for the same.

Benefits

No response

Add ScreenShots

No response

Priority

High

Record

• I have read the Contributing Guidelines
• I'm a GSSOC'24 contributor
• I have starred the repository

[github-actions]

Hi @navyabijoy! Thanks for opening this issue. We appreciate your contribution to this open-source project. Your input is valuable and we aim to respond or assign your issue as soon as possible. Thanks again!

[github-actions]

Hello @navyabijoy! Your issue #3568 has been closed. Thank you for your contribution!