📊 Better Forecasts. Smarter Decisions.
Priya Banerjee
Data Scientist | NLP, forecasting, Python | Ex-researcher | Women in Tech mentor
📊 Better Forecasts. Smarter Decisions.
One of the most interesting challenges in data science is turning historical data into actionable business insights.
Recently, I worked on a retail demand forecasting project focused on improving prediction accuracy and supporting smarter inventory decisions.
The journey involved:
🔹 Data preparation and feature engineering
🔹 Exploring demand patterns and seasonality
🔹 Building and evaluating machine learning models
🔹 Measuring performance using Mean Absolute Percentage Error (MAPE)
One key takeaway: a model isn't valuable just because it makes predictions. It becomes valuable when its predictions help businesses make better decisions.
As highlighted in my project, forecast error improved from 18% to 9% MAPE.
This reinforced my belief that good data science combines technical expertise, experimentation, and a clear understanding of business problems.
💬 Data science community: What techniques have helped you improve forecasting accuracy in your projects?
#DataScience #MachineLearning #Python #DemandForecasting #DataAnalytics
#datascience#machinelearning#python#demandforecasting#dataanalytics
