By the end of the book, the readers will have an understanding of different deep learning approaches, models, pre-trained models, and familiarity with the implementation of various deep learning algorithms using various frameworks and libraries.
This book demystifies deep learning and AI, making complex concepts accessible to all readers. It blends theory with practical... Læs mere
XVA Analysis: Probabilistic, Risk Measure, and Machine Learning Issues offers readers an up-to-date and comprehensive exploration of the X-Value Adjustment (XVA) universe and of the embedded risk measure issues inherent within it.
This book explains the complete loop to effectively use self-tracking data for machine learning. While it focuses on self-tracking data, the techniques explained are also applicable to sensory data in general, making it useful for a wider audience.
This volume first explores the potential of machine translation of literature; goes on to explore possibilities for artificial literary... Læs mere
Today's online and offline world is an immensely complex system. Introduction to Online Complexity attempts to quantitatively address the phenomena arising out of the new science of interaction between humans, technology, and AI systems.
This concise single-semester textbook demonstrates cutting-edge concepts at the intersection of machine learning (ML) and wireless communications. Requiring... Læs mere