Using Machine Learning with Python, and supplemental materials

Build the ML the using K-Nearest Neighbors Model with Scikit-learn

Understand the role of linear regression analysis You are expected to have the following components:

1. Loading and exploring the iris dataset 2. Building your first model: k nearest neighbors 3. Making predictions 4. Evaluating the model

You need to submit a complete Jupyter notebook (.ipynb) file with all the source codes, outputs/charts, and necessary texts/comments in markdown cells:

1. Run All required steps for the lab before submitting your file to make sure there is no error in your codes

2. Make sure that you have all libraries and modules properly imported before you use them.

3. Use proper formatting for your markdown cells and comments in your lines of code

4. Conclude your file with your own answers to What are the strengths and weaknesses of kNNs?.