In the film industry, movie ratings are now a vital predictor of box office success. For personalized recommendation systems, which rely on reliable and effective models to produce accurate results, accurate prediction of these ratings is also essential. Using the IMDb dataset, this study investigates the use of machine learning techniques in movie rating analysis and recommendation systems to forecast movie rating categories and produce customized movie recommendations. A brief comparison with deep learning architectures is also provided. The results of this study provide a useful resource for future developments in movie rating prediction, assisting practitioners and researchers in enhancing recommendation systems’ efficacy.
This paper compares four machine learning models for predicting residential property prices in Addis Ababa, Ethiopia. The models tested are Linear Regression, Ridge Regression, Random Forest, and Gradient Boosting, evaluated using MAE, RMSE, R2, and 5-fold cross-validation. The s…
Abstract: This study examines the determinants and predictive accuracy of financial distress for seven mature market economies: Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States. The aim is to assess whether distress can be predicted through a unifo…
The cardiovascular (Cardiac) disease (CVD) is another factor that causes death among the global population most, and this is the reason why there is a high necessity to implement proper, effective, and interpretive diagnostic systems. The usage of machine learning (ML), deep lear…
This dataset contains the supplementary numerical data generated and analysed in the study entitled: "Bearing Capacity and Safety Factors of Ring Foundations in Spatially Variable Soils: A Hybrid FELA-Machine Learning Approach." The dataset supports the investigation of ring foun…
## ALTERNATIVE TITLES ### Alternative Title 1 (Comprehensive)**"AI-Driven Analysis of Cube {100}<001> and Goss {110}<001> Textures: Machine Learning, Deep Learning, and Generative Models for Crystallographic Texture Quantification in Metallurgical Engineering"** ### Alternative T…