Machine Learning Model for Order Demand Prediction based on historical Order data - Built for Swiggy Hackathon 2018
-
Updated
Jul 16, 2018 - Python
Machine Learning Model for Order Demand Prediction based on historical Order data - Built for Swiggy Hackathon 2018
Integrated real-time data analytics for optimized public transport, innovative road monitoring using demand prediction, and conditioning tech for sustainability, real time pothole detection either by image or video, smart parking count system for efficiency using AI/ML.
A spare engine placement generator based on a Finite-Horizon Markov Decision Process
An AI-based inventory optimization system that leverages machine learning to predict demand, recommend menu items, and streamline stock management for restaurants and food service businesses.. — all deployed through a real-time Stream lit web app.
Dynamic Pricing is an application of data science that involves adjusting the prices of a product or service based on various factors in real time. It is used by companies to optimize revenue by setting flexible prices that respond to market demand, demographics, customer behaviour and competitor prices.
A default spare engine placement generator
NYC Taxi demand forecasting using machine learning and weather analytics. Includes end-to-end pipeline: data preprocessing, feature engineering, XGBoost forecasting, and Power BI dashboards.
Code for the ASET 2025 paper: "DemandLens: Enhancing Forecast Accuracy Through Product-Specific Hyperparameter Optimization".
Add a description, image, and links to the demand-prediction topic page so that developers can more easily learn about it.
To associate your repository with the demand-prediction topic, visit your repo's landing page and select "manage topics."