Generating point forecasts for future daily sales based on historical sales data.

Primary aim of this project is to build machine learning model that give the should able to predict the sales of the different stores of Big Mart according to the provided dataset.

Sales Prediction : Predicting sales of a major store chain Rossmann; Rossmann operates over 3,000 drug stores in 7 European countries. Currently, Rossmann store managers are tasked with predicting their daily sales for up to six weeks in advance. Store sales are influenced by many factors, including promotions, competition, school and state holi…

Different algorithms for forecasting sales and finding the predictive value of ongoing trends and also predict the future forecasting

The motivation of this project is to complete the course in Data Science from HarvardX. The project aims to predict the units sold for each specific product. The database was downloaded from Kaggle and consists of data from e-commerce platform Wish (https://www.wish.com). Wish is a retailer that sells millions of product to customers in a e-comm…

Forecasting time series data using Holt Winter's Model in Python

Develop a data science project using historical sales data to build a regression model that accurately predicts future sales. Preprocess the dataset, conduct exploratory analysis, select relevant features, and employ regression algorithms for model development. Evaluate model performance, optimize hyperparameters, and provide actionable insights.

Develop a data science project using historical sales data to build a regression model that accurately predicts future sales. Preprocess the dataset, conduct exploratory analysis, select relevant features, and employ regression algorithms for model development. Evaluate model performance, optimize hyperparameters, and provide actionable insights.

Develop a data science project using historical sales data to build a regression model that accurately predicts future sales. Preprocess the dataset, conduct exploratory analysis, select relevant features, and employ regression algorithms for model development. Evaluate model performance, optimize hyperparameters, and provide actionable insights.

Sales forecasting ML repository for Walmart Sales, leveraging machine learning and data analysis techniques to predict future sales and optimize business strategies.

Engaged in a collaborative effort with a company seeking to implement machine learning for forecasting purposes. Employed Time Series Analysis using data spanning 2019 to 2023, evaluating three distinct models. The model with the optimal error score was selected to project values for 2024.

Prediction of quarterly sales of a company using XGBoost Regression Model using python and multiple Data Science Libraries.

It is a sales forecasting web app that processes sales data, generates forecasts, and displays the forecast results with performance metrics as graphs. You can download these graph statistics as a PDF report, export the forecast data as a CSV file, and analyze the forecast data in a Power BI dashboard.