Machine learning models can be incredibly valuable tools for business leaders. They can aid in interpreting historic data, making decisions for future initiatives, helping to improve the customer ...

In addition to novel algorithms, machine learning places great emphasis on model checking (through holdout samples and cross-validation) and model shrinkage (adjusting predictions toward the mean to ...

Machine learning plays a pivotal role in the development of autonomous vehicles and robots. In the realm of mechanical ...

List of best Machine Learning Models for time series forecasting, Stock Prediction, Multiclass Classification, Regression, Small Datasets, Big Datasets, etc.

Machine learning is an increasingly important and controversial topic in quantitative finance. A lively debate persists as to whether machine learning techniques can be practical investment tools.

This fundamental (and quite reasonable) limitation of any machine learning technique is addressed by feature selection: choosing a good set of features upon which to build models.

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

Donor selection practices for matched unrelated donor (MUD) hematopoietic cell transplantation (HCT) vary, and the impact of optimizing donor selection in a patient-specific way using modern machine ...