About the Journal

International Journal of Machine Learning and Predictive Analytics (IJMLPA) is an international, peer-reviewed academic journal dedicated to publishing high-quality research that spans multiple disciplines. The journal provides a platform for researchers, academicians, industry professionals, and scholars to share innovative ideas, emerging trends, and practical solutions that address complex challenges through interdisciplinary approaches in machine learning and predictive analytics and their core technologies.

 

Focus and Scope

 

• Supervised and Unsupervised Learning
• Deep Learning and Neural Networks
• Reinforcement Learning
• Transfer Learning and Meta-Learning
• Ensemble Learning Methods
• Time Series Forecasting
• Predictive Modeling and Risk Analysis
• Classification and Regression Techniques
• Anomaly Detection
• Decision Support Systems
• Statistical Learning and Bayesian Methods
• Data Mining and Pattern Discovery
• Feature Engineering and Dimensionality Reduction
• Probabilistic Models
• Data Preprocessing and Cleaning
• Big Data Analytics and Scalable ML Systems