Assignment Intructions:

Now that you have been equipped with the skills to use different Machine Learning algorithms, over the course of five weeks, you will have the opportunity to practice and apply it on a dataset. In this project, you will complete a notebook where you will build a classifier to predict whether a loan case will be paid off or not.

You load a historical dataset from previous loan applications, clean the data, and apply different classification algorithm on the data. You are expected to use the following algorithms to build your models:

• k-Nearest Neighbour
• Decision Tree
• Support Vector Machine
• Logistic Regression

The results is reported as the accuracy of each classifier, using the following metrics when these are applicable:

• Jaccard index
• F1-score
• LogLoass

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Setup Instructions:

A-Create an account in Watson Studio if you dont have (If you already have it, jump to step B).

• Browse into https://www.ibm.com/cloud/watson-studio
• Click on 'Start your free trial'
• Enter your email, and click 'Next'
• Enter your Name, and choose a Password. Then click on 'Create Account'
• Go to your email, and confirm your account.
• Click on 'Proceed'
• In "Select Organization and Space" form, leave everything as default, and click on 'Continue'
• It is done. Click on 'Get started!'

B-Sign in into Watson Studio and import your notebook

• Sign in into https://www.ibm.com/cloud/watson-studio
• Click on 'New Project'
• Select 'Data Science' as type of project.
• Give a name to your project, and a description for your reference, then setup your project as following and click "Create".

Notice 1: because you are going to share this project with your peer for evaluation, please make sure you have unchecked Restrict who can be a collaborator

Notice 2: You have to create an IBM Object Storage, if you dont have any IBM Object Storage (you can use the free Lite plan)

• From the top-right, Click on 'Add to project', and then select 'Notebook'. C

• In the 'New notebook' form, click on 'From URL', and enter the Notebook URL: https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/ML0101ENv3/labs/ML0101EN-Proj-Loan-py-v1.ipynb

• Give the notebook a proper name and description and click on Create Notebook to initialize the notebook

C. Complete the notebook

• Start running the notebook
• Complete the notebook based on the description in the notebook.