July 27, 2022
10.00 AM To 02.00 PM

Demand Forecasting using Deep Learning

July 27, 2022

10.00AM To 02.00PM

Overview

Demand Forecasting is a technique of predicting the future based on the analysis of data and events from the past. It will help to reduce the uncertainty of the demand future. Since future is uncertain no one will be able to exactly predict the future. But a good forecasting system will reduce the amount of uncertainty in the future and thereby reducing the risk. Demand Forecasting is an important input to supply chain management. It improves the efficiency of supply chain by accurately managing the Safety Stock, Reorder level and increases the transparency of the supply chain. One can handle the disruptions better with efficient demand planning. This will also help to reduce the supply chain risk.

Deep Learning with what we call Recurrent Neural Networks are able to map complex data generating process but also remember how much old information to be dropped when new information enters the system. Earlier forecasting techniques have limitations in handling variety of data sources like Customer reviews , Click stream data , CRM Systems data in the form of voice , Social media interaction etc

There are three major forecasting categories. They are Economic Forecasts, Technology Forecasts & Demand forecasts. There are slight variations in the techniques used but about 60-70% are common. For this master class we will focus on demand forecasting.

Workshop Schedule

Introduction to forecasting
Introduction to Basics of Machine Learning-Neural Network & Decision tress
Fundamentals of Deep Learning , Recurrent Neural Networks and their applicability in Forecasting
Use case demo of Demand Forecasting using KNIME DEEP LEARNING capabilities using real life data set