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Automotive industry - All Analysis about Car

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📊 Overview of the App

Welcome to AutoCARs. Here you can get a complete analysis and recent trends about all types of Car in Automotive Industry. You can demonstrate how the Automotive Industry could harness data to take informed decisions. The project aims to perform various visualizations and provide various insights from the considered Indian automobile dataset by performing data analysis that utilizing machine learning algorithms in Python programming language. The considered dataset is of Indian cars that consists of various features. The insights that could be estimated from this dataset would be feature such as price of a specific car model that could be estimated using the other attributes of that particular car model using machine learning algorithms.
The secions include:-

1. Car Sales Analysis in Ukraine

2. Car Sales Analysis in US

3. Predict Used Car Price

🚀 Tech Stack:

image   image   Plotly image   image   image   image   image   image  

Structure Of The Project

  • The home page consists of an about section, a services section and a contact section where in the section you will find three options i.e, car Sales Analysis in Ukraine, Car Sales Analysis in US and Car Price Prediction.
  • In the first section, there is Car Sales Analysis in Ukraine where there are different queries answered related to recent Car Sales in Ukraine in form of different visualization using Plotly.
  • The next section consists of Car Sales Analysis in US where different quires are answered in form of visualization related to Car Sales in US. The user get to know about the different trends in automotive industry.
  • Using the above two analysis, we can get a complete understanding about the automotive industry.
  • The last section consistes of Used Car price prediction where the Machine Learning Model uses the Lasso Regression to predict the price of the car.
  • The prediction section consists of forms which take few different feature as input from the user in a given specified range. The most relevant features are taken into consideration for prediction also these features
  • So the user can get a complete analysis of the current trends related to automotive industry and Car sales.

Model Deployment

  • The web application is built using python library -> Flask and Web Programming languages -> HTML, CSS, Bootstrap
  • The entire application is finally deployed on Heroku by adding - Procfile (informs Heroku that which application is to be run first), Requirements (notifies Heroku about the libraries that needs to be installed before deploying or running our application)
  • See the deployed application here.

Demo Video Link : https://youtu.be/WyZ1jjIudDo

🔴 UI Of The Web Application

1. Home Page

2. About Us

3. Services Section

4. Car Sales Analysis in Ukraine Section

5. Car Sales Analysis in US Section

6. Car Price Prediction Section

7. Contact Section

Run Locally

Open VSCode -

1.1 git clone <repo link>

1.2 cd Data-Analysis

1.3 pip install -r requirements.txt

1.4 flask run