Sequence Learning with RNN: A practical approach to Retail Sales Forecasting

In this expert-led session, you’ll see how RNNs (using LSTM) are applied end-to-end for retail sales forecasting, from preparing sequential data to building, training, and evaluating a forecasting model.

The focus is on practical implementation and interpretation, not just theory.

What You’ll Learn

• How retail sales forecasting fits naturally into sequence learning
  
• Preparing time-series data for RNNs 
  
• Building an LSTM-based forecasting model
  
• Evaluating predictions using business-relevant metrics
  
• Interpreting forecasts and understanding model limitations
  

By the end of this session, you’ll have a working LSTM-based retail sales forecasting pipeline that takes historical sales data, produces future forecasts, and evaluates predictions using business-relevant metrics.

Who Should Attend?
This session is ideal if you:

• Already understand basic RNN / LSTM / GRU concepts
  
• Want to see how RNNs are actually used for time-series forecasting
  
• Are interested in retail analytics, demand forecasting, or business prediction

Pre-Requisites

• Prior exposure to RNNs, LSTM, or GRU
  
• Basic familiarity with time-series or sequential data
  
• Comfort with fundamental deep learning concepts