An E-Commerce company based in Iowa that sells clothing online but they also have in-store style and clothing advice sessions. Customers come in to the store, have sessions/meetings with a personal stylist, then they can go home and order either on a mobile app or website for the clothes they want.
The company is trying to decide whether to focus their efforts on their mobile app experience or their website.
The dataset is downloaded from the Kaggle. Also the dataset is attached in the Repository.(link)
Working with the Ecommerce Customers csv file from the company. It has total 8 columns - Customer info such as Email, Address, and their color Avatar. Then it also has numerical value columns:
- Avg. Session Length: Average session of in-store style advice sessions.
- Time on App: Average time spent on App in minutes.
- Time on Website: Average time spent on Website in minutes.
- Length of Membership: How many years the customer has been a member ?
- Yearly Amount Spent: How much amount the customer have spent ?
- Importing the required libraries
- Reading the dataset
- Exploratory Data Analysis (EDA)
- Visualizing Data using Seaborn library
- Data Modeling
- Separating the data into features and target variable.
- Splitting the data into training and test sets.
- Implementing the Linear Regression Model.
- Evaluating the prediction scores.
- Visualizing the results
- Evaluating the model accuracy.