Retail store forecasting

Imagine you are working as a machine learning engineer and your company just landed a new project. A rapidly growing superstore in Florida wants your help. They want to predict future reviews, as this will serve as a guide in planning the expansion of their stores to meet the expected demand. You have been saddled with the responsibility of building a forecasting model with the available historical data provided by the Tensor superstore. Let’s jump in and see how you can solve this problem, as your company is counting on you. Let’s get started!

1. We begin by importing the necessary libraries for our project:

   import pandas as pd

   import numpy as np

   import matplotlib.pyplot as plt

   Here, we import numpy and matplotlib for numerical analysis and visualization purposes and pandas for data transformations.

2. Next, we load the time series data:

   df = pd.read_csv('/content/sales_data.csv')

   df.head()

   Here, we load the data and use the head function...