Prediction using Decision Tree Algorithm | Task #6 (TSF)

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I'm glad to post my task (#task6) as part of the internship through Graduate Rotational Internship Program (#GRIP) in April 2021 organized by The Sparks Foundation.

In this task, I have constructed a decision tree to predict the right classes from any dataset and shown the tree graphically, the model can perform best on both training and testing datasets.

Programming Language used - #python
IDE used - #anaconda
Tool used - #jupyter Notebook
Library supports - #numpy, #pandas, #scikitlearn, #matplotlib, #seaborn

Have a look at my insights shared on the following platforms,
  1. Akash Gohil
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