Scope of Submission
We welcome submissions from a broad range of disciplines, including but not limited to:
- Advanced machine learning techniques
- Deep learning models in data science
- Ensemble methods for predictive analytics
- Feature selection in machine learning
- Model evaluation and validation techniques
- Transfer learning applications in data
- Unsupervised learning in big data
- Reinforcement learning in practice
- Machine learning for time series data
- Ethics of machine learning applications
- Explainable AI in data science
- Big data challenges for machine learning
- Applications of neural networks
- Machine learning in finance analytics
- Data preprocessing for machine learning
- Scalable machine learning algorithms
- Applications of AI in industry
- Collaborative machine learning frameworks
- Future directions in machine learning
- Machine learning for social good
All papers must be original and not previously published or submitted elsewhere.
