Use Machine Learning Python modules and algorithms to solve problems using data sets.

 

Also a summary 700 word of what you have learned from the dataset. Include in your summary the testing you did in your program. Topics for your summarization could include but are not limited to:

What did you learn from the data?

Which algorithms did you use?

What problem did you solve?

a. Classification b. Regression

c. Something else?

Did you use more than one algorithm?

Did you use an algorithm of the same type to test for efficiency?

Did you implement any hyperparameter tuning?

 

 

 

Transcribed Image Text:

15.15 (Linear Regression with the Diabetes Dataset) Investigate the Diabetes dataset bundled with scikit-learn https://scikit-learn.org/stable/datasets/index.html#diabetes-dataset Exercises 661 The dataset contains 442 samples, each with 10 features and a label indicating the "dis- ease progression one year after baseline." Using this dataset, reimplement the steps of this chapter's multiple linear regression case study in Section 15.5. 15.15 (Linear Regression with the Diabetes Dataset) Investigate the Diabetes dataset bundled with scikit-learn https://scikit-learn.org/stable/datasets/index.html#diabetes-dataset Exercises 661 The dataset contains 442 samples, each with 10 features and a label indicating the "dis- ease progression one year after baseline." Using this dataset, reimplement the steps of this chapter's multiple linear regression case study in Section 15.5.

Answer rating: 100% (QA)

Title Exploring the Diabetes Dataset with Machine Learning Summary In this exploration we delve into the Diabetes dataset provided by scikitlearn consisting of 442 samples each containing 10 features ... View the full answer