Forecasting Walmart Sales

In this project I will use data from the Kaggle competition: Walmart Recruiting - Store Sales Forecasting. The goal of this project is to build an useful machine learning model that can predict sales with resonable accuracy based on historic sales data. This individual project is part of the requirements of the Machine Learning with Python: Zero to GBMs course, a free, online certification course, hosted on Jovian.

1 - Downloading and importing the necessary modules and the dataset

!pip install opendatasets jovian numpy pandas matplotlib seaborn scikit-learn pyarrow xgboost

import os
import opendatasets as od
import jovian
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
import joblib
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import MinMaxScaler
from sklearn.preprocessing import OneHotEncoder
from sklearn.ensemble import RandomForestRegressor
from xgboost import XGBRegressor

%matplotlib inline
matplotlib.rcParams['font.size'] = 14
sns.set_style('whitegrid')