Feature engineering involves systematically transforming raw data into meaningful and informative features (predictors). It is an indispensable process in machine learning and data science. This ...

More information: Maxwell T. West et al, Drastic Circuit Depth Reductions with Preserved Adversarial Robustness by Approximate Encoding for Quantum Machine Learning, Intelligent Computing (2024).

Fundamentals: Your Foundation for Success Before diving into advanced tools and techniques, it’s crucial to prioritize mastering the fundamentals of machine learning. A solid grasp of core ...

The latest version of Stata introduces a wealth of substantive new features. Expanded machine learning – In Stata 19, you can build high-performance predictive models with the all-new H2OML ...

This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms. All methods ...