There are 12 repositories under sales-forecasting topic.
List of papers, code and experiments using deep learning for time series forecasting
Time Series Decomposition techniques and random forest algorithm on sales data
Machine Learning for Retail Sales Forecasting — Features Engineering
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, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models
Full-stack Highly Scalable Cloud-native Machine Learning system for demand forecasting with realtime data streaming, inference, retraining loop, and more
使用LSTM预测商品销量,考虑销量激增点影响
Consumer Buying pattern Analysis and Sales Forecasting using Artificial Intelligence.
A detialed analysis on the customers, products, orders and shipments of the Brazilian E-commerce giant Olist.
Machine Learning Outperforms Classical Forecasting on Horticultural Sales Predictions
Exponential Smoothing, SARIMA, Facebook Prophet
Example of Sales Forecasting
Empower decision-makers with an interactive Power BI dashboard showcasing e-commerce performance metrics and trends. Analyze sales data, forecast future trends, and drive informed strategies for business growth.
Machine learning algorithms applied on the Online retail dataset provided by UCI Machine learning 🤖
Retail Sales Forecasting and Monitoring project offers real-time analysis and forecasts for retail sales.
How much camping gear will individual Walmart stores sell each month in a year? To the uninitiated, calculating sales at this level may seem as difficult as predicting the weather. Both types of forecasting rely on science and historical data. While a wrong weather forecast may result in carrying around an umbrella on a sunny day, inaccurate business forecasts could result in actual or opportunity losses. In this competition, in addition to traditional financial forecasting methods, we challenged to use machine learning to improve forecast accuracy.
This repository serves as a showcase of the skills I've acquired through Datacamp's "Data Analysis in Excel" course.
Sales forecasting with random forest, decision tree. Promotion effect calculation.
Exploring the efficacy of statistical and econometric methodologies for sales forecasting, this repository provides a comprehensive analysis alongside code implementations, offering empirical insights to guide decision-making in the retail industry.
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 for future sales of each store-item combination.
An example of multi-variate time-series prediction
Understanding how well a product that is published on the E-Commerce platform Wish is going to sell using Machine Learning.
MSc thesis about sales forecasting in high-dimensional contexts taking into account product relationships and promotions
Forecast store sales using the Facebook Prophet algorithm
Time Series Forecasting
Build a forecasting model to predict the sale of a store.
SuperStore Sales analysis in Power BI with forecasting of upcoming 15 days sales
This dashboard forecasts sales for the next 12 months with 95% confidence level. It also looks at the region where most sales is achieved, cities with the most sales and the top 5 customers in 2017.
Sales Data Analysis and Forecasting Using Ensemble Methods
This repository contains the code and data for analyzing pizza sales using SQL Server as the data store and Power BI for data visualization and analysis. Explore sales trends, customer preferences, and more to gain insights into pizza sales using this repository.
By Utilizing Data Analysis Techniques, specially focusing on Time Series Analysis, to provide valuable insights and accurate sales forecasting
Enable stakeholders with an engaging Power BI dashboard illustrating key e-commerce performance indicators and patterns. Evaluate sales data, predict forthcoming trends, and formulate knowledgeable approaches to foster business expansion.
Comprehensive Jupyter notebook designed for analyzing and predicting pharmaceutical sales with PySpark
CM3070 Final Project Repository
Time series forecasting using Prophet and PySpark for parallelized model training.