Demand Forecasting and Comparative Performance analysis Performed with Hybrid CNN-LSTM Deep Learning Model for Business

The purpose of this project is to
perform forecasting and comparative analysis
using historical data. Demand forecasting plays
a major role in business decisions making,
especially in inventory management and supply
chain optimization. Forecasting helps
organizations predict future trends and make
better decisions. In this project, different models
from Machine Learning and Deep Learning are
used to predict future values. The perfomance
of these models is compared based on accuracy
and error metrics. This results help to identify
the most efficient model for forecasting .This
project proposes a hybrid deep learning model
combining convolution neural networks(CNN)
and long short term memory(LSTM) to improve
forecasting accuracy.