Wyniki wyszukiwania:

"The Fundamentals of Machine Learning" is designed to be accessible to readers with a basic understanding of mathematics and programming. We start with an introduction to the key concepts, exploring the different types of machine learning algorithms and their applications. From there, we delve into the essential building blocks, including data preprocessing, feature engineering, model selection, and evaluation. We also cover important topics such as overfitting, regularization, and cross-validation to help you develop models that generalize well.It is important to note that machine learning...

The present work of our book is devoted to the study of common fixed points for single and multivalued mappings in nonlinear analysis. In the present work we obtain some common fixed point theorems in some of recently defined metric structures, like: cone metric spaces, fuzzy metric spaces, non-Archimedean PM-spaces and complex valued metric spaces by using different contractive conditions.The book ends with common fixed point of mappings satisfying rational inequality in complex valued metric spaces.