Full-stack Highly Scalable Cloud-native Machine Learning system for demand forecasting with realtime data streaming, inference, retraining loop, and more

Machine Learning for Retail Sales Forecasting — Features Engineering

Time Series Decomposition techniques and random forest algorithm on sales data

Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAP…

A detialed analysis on the customers, products, orders and shipments of the Brazilian E-commerce giant Olist.

AI-Powered Bookkeeping & Demand Forecasting

This project focuses on time series forecasting to predict store sales for Corporation Favorita, a large Ecuadorian-based grocery retailer. The goal is to build a model that accurately predicts the…

Time Series Forecasting of Walmart Sales Data using Deep Learning and Machine Learning

Sales Time Series Forecasting using Machine Learning Techniques (Random Forest, XGBoost, Stacked Ensemble Regressor)

Retail Sales Forecasting and Monitoring project offers real-time analysis and forecasts for retail sales.

This project predicts the sales demand for various items in different stores based on historical sales data. The objective is to develop a machine learning model that can provide accurate forecasts…

Time Series Forecasting Problem