/Big-Mart-Sales-Prediction

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Big Mart Sales Prediction End-to-End project

Big Mart Sales Prediction

What is Big Mart sales prediction? Bigmart Sales Prediction is a regression problem where we have to analyze and predict the sales of Bigmart based on various aspects of the dataset. The objective is to build a predictive model and discover the sales of each product at their respective store.

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Data Information

Sales Prediction for Big Mart Outlets The data scientists at BigMart have collected 2013 sales data for 1559 products across 10 stores in different cities. Also, certain attributes of each product and store have been defined. The aim is to build a predictive model and predict the sales of each product at a particular outlet.

Using this model, BigMart will try to understand the properties of products and outlets which play a key role in increasing sales.

Please note that the data may have missing values as some stores might not report all the data due to technical glitches. Hence, it will be required to treat them accordingly.

Data Dictionary We have a train (8523) and test (5681) data set, the train data set has both input and output variable(s). You need to predict the sales for the test data set.

Train file: CSV containing the item outlet information with a sales value

Variable Description

  • Item_Identifier ---- Unique product ID
  • Item_Weight ---- Weight of product
  • Item_Fat_Content ---- Whether the product is low fat or not
  • Item_Visibility ---- The % of the total display area of all products in a store allocated to the particular product
  • Item_Type ---- The category to which the product belongs
  • Item_MRP ---- Maximum Retail Price (list price) of the product
  • Outlet_Identifier ---- Unique store ID
  • Outlet_Establishment_Year ---- The year in which the store was established
  • Outlet_Size ---- The size of the store in terms of ground area covered
  • Outlet_Location_Type ---- The type of city in which the store is located
  • Outlet_Type ---- Whether the outlet is just a grocery store or some sort of supermarket
  • Item_Outlet_Sales ---- sales of the product in t particular store. This is the outcome variable to be predicted.

Test data As same as train data

Dataset

Tech Stack Used

  • pandas
  • numpy
  • matplotlib
  • seaborn
  • sklearn
  • flask
  • HTML
  • Bootstrap

image

After Predict

Screenshot (4)

To access this project

Setup 1: Clone the repo

https://github.com/shailesh2210/Kidney-disease-prediction.git

Step 2- Create a conda environment after opening the repository

conda create -n venv python=3.8 -y
conda activate venv

Step 3 - Install the requirements

pip install -r requirements.txt

Step 4 - Run the application server

python app.py

Author

Shailesh Gaddam

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