Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. Multiple techiniques have been provided in this repository.
The algorithms have been implemented using Python. Libraries used are:- Pandas, NumPy, Statsmodel, Autoarima, Matplot, Plotly.
SMA_SES_DES.py contains the code for EDA and then Simple Moving Average, Single Exponential Smoothing and Double Exponential Smoothing.
ARIMA.py contains the code for Auto Regressive Integrated Moving Average implementation and SARIMAX contains the code for Seasonal Auto Regressive Integrated Moving Average with Exogenous Variables.