Aim and Scope
The aim of the Sage Science Review of Applied Machine Learning is to provide a platform for researchers, practitioners, and scholars to share their innovative research and applications in the field of machine learning. The journal seeks to promote the advancement of applied machine learning by publishing high-quality and original research papers, reviews, and case studies.
The scope of the journal includes a broad range of topics related to applied machine learning, including but not limited to:
- Machine learning algorithms and models
- Deep learning and neural networks
- Natural language processing
- Computer vision and image processing
- Data mining and knowledge discovery
- Statistical learning
- Reinforcement learning
- Transfer learning
- Explainable and interpretable machine learning
- Machine learning for healthcare, finance, social media, and other applications
The journal welcomes submissions from both academia and industry and encourages interdisciplinary research that combines machine learning with other fields such as engineering, biology, psychology, and economics. The Sage Science Review of Applied Machine Learning aims to contribute to the advancement of applied machine learning and its impact on society.
