List of papers, code and experiments using deep learning for time series forecasting
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Updated
Mar 16, 2024 - Jupyter Notebook
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
A detialed analysis on the customers, products, orders and shipments of the Brazilian E-commerce giant Olist.
Consumer Buying pattern Analysis and Sales Forecasting using Artificial Intelligence.
Exponential Smoothing, SARIMA, Facebook Prophet
Machine Learning Outperforms Classical Forecasting on Horticultural Sales Predictions
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.
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 unit sales for thousands of items sold at different Favorita stores.
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.
Machine learning algorithms applied on the Online retail dataset provided by UCI Machine learning 🤖
Example of Sales Forecasting
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.
Sales forecasting system w/ dashboard using SARIMAX model
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 bus…
Users business cases in python
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