End-to-end demand forecasting with Python using synthetic time-series sales data. Includes data generation, cleaning, ARIMA/SARIMA model selection by AIC, evaluation with RMSE and MAPE, and 90-day forecasts with confidence intervals. Reproducible scripts and visualizations for portfolio showcase.

A project focused on YouBike optimization, including improvement of dispatch strategies and prediction of potential demand.

Bike sharing prediction based on neural nets

Machine Learning Outperforms Classical Forecasting on Horticultural Sales Predictions

Minimize forecast errors by developing an advanced booking model using Python

Applying a structural time series approach to California hourly electricity demand data.

AI-Powered Bookkeeping & Demand Forecasting

ARIMA ML Model - Oil and Gas Supply Chain Demand Forecasting with LLM Analysis using AWS Bedrock Foundational Model

2018 Lpoint Big Data Competition

E-commerce pricing optimization & dynamic user profiling

A comprehensive Streamlit dashboard for optimizing supply chain operations. Features interactive analytics for demand forecasting, inventory management, and supplier performance.

A demand forecasting pipeline deployed on Azure and AWS

🚀 Machine Learning Integration Leverage ARIMA and SARIMA models for time-series forecasting, fully deployed using Streamlit for quick and accurate predictions.

🌌 ChaosChain-AI: Next-Gen Supply Chain AI Simulator Advanced AI control tower combining chaotic demand modeling, Monte Carlo simulations, and multi-factor risk scoring. Features real-time monitoring, predictive analytics, and automated mitigation across global supply chains. 🔬 Research | 🏭 Supply Chain AI | 🤖 Machine Learning |📊 Simulation

A computer system that can predict consumer demand for the fast food sector.

A simple application that demonstrates the power of PredictHQ's APIs.

SKU-level customer demand forecasts for SSDs for improved long-term supply planning

OptiChain is an AI-powered supply chain optimization platform that uses reinforcement learning and simulation to improve inventory management, demand forecasting, and logistics efficiency.

Retail-Forecast — tools, notebooks, and models for demand forecasting and time-series analysis 📈🧠 Designed for retail use-cases (sales, promotions, inventory) with reproducible pipelines and experiments 🛒🔁

Neuroplasticity-inspired method for multi-tasking in demand forecasting scenarios on vast datasets.