This project aims to predict house prices using the Ames Housing dataset. The goal is to preprocess the data, train a stacking model with multiple base models, and ...

A Machine Learning Project implemented from scratch which involves web scraping, data engineering, exploratory data analysis and machine learning to predict housing prices in New York Tri-State Area.

In today’s data-driven world, enterprises face numerous challenges in extracting insights from data for informed decision making. Traditional approaches often fall short when handling the complexity ...

Predictive models turn historical data into reliable forecasts that support accurate planning across industries. Different modeling types solve different problems, from forecasting numbers to ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. No ...

1 Urban Governance and Design Society Hub, Hong Kong University of Science and Technology, Guangzhou, China. 2 School of Accounting and Finance, Faculty of Business, The Hong Kong Polytechnic ...

The investors’ dream of forecasting the stock market is typically considered to be just that: an unrealistic aspiration. However, we find that forecasting stock performance may in fact not be ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...

1 School of Fashion Design and Engineering, Zhejiang Sci-Tech University, Hangzhou, China. 2 School of Science, Zhejiang Sci-Tech University, Hangzhou, China. Reliable sales forecasts are important to ...