Minor Project: Deploying a Machine Learning Pipeline on Cloud

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Table of Contents

1. Introduction
2. Initial Plan
3. The Dataset
4. Pairplot
5. Heat Map
6. Feature Importance
7. Web Application
8. Tableau Dashboard
9. Resources
10. Motivation

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Machine Learning Pipeline on Cloud

The aim of this project is to create a Machine Learning Model and deploy it on a Cloud Application and create a Web Application for accessing it through internet.

We will be using a simple dataset of used vehicles for our model and try to predict the price of a vehicle depending values of the features specified by the user/buyer.

Click here to view the Machine Learning Pipeline.

Click here to view the Web Application.

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Initial Plan:

• 1. Load the dataset
• 2. Perform EDA on the dataset
• 3. Generate Plots and visuals
• 4. Select a suitable Machine Learning Model
• 5. Create a Tableau Dashboard
• 6. Develop a Web App using Flask
• 7. Create a single/double webpage site for the Web App
• 8. Deploy the project on Heroku

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The Dataset

*a preview of the dataset

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Pairplot

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Heat Map

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Feature Importance

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Web Application

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Tableau Dashboard

*You can access the interactive dashboard here

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Resources

• Vehicle Dataset
• Random Forest Regressor

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Motivation

• Redapt report
• Venture beat report