This book offers a comprehensive discussion of the Bayesian inference framework and demonstrates why this probabilistic approach is ideal for tackling the various modelling pro...Loe edasi...
Learning is an empirical phenomenon whereby people or organisations undergo a level of efficiency improvement with recurring tasks. Alan Jones pragmatic guide to this important element within estimating introduces two key learning curve models: Wr...Loe edasi...
Presenting a cutting-edge critical analysis of how data, algorithms and surveillance are changing the face of contemporary higher education, this open access book explores the role of big data and learning analytics to provide new insights into th...Loe edasi...
Handbook of Statistical Analysis: AI and ML Applications, Third Edition, is a comprehensive introduction to all stages of data analysis, model building and implementation, and useful to students and professionals across a variety of fields...Loe edasi...
Classification problems are common in business, medicine, science, engineering and other sectors of the economy. Data scientists and machine learning professionals solve these problems through the use of classifiers. Choosing one of these data dri...Loe edasi...
Classification problems are common in business, medicine, science, engineering and other sectors of the economy. Data scientists and machine learning professionals solve these problems through the use of classifiers. Choosing one of these data dri...Loe edasi...
This book provides a conceptual introduction to regression and machine learning and its applications in education research. The book discusses its diverse applications, including its role in predicting future events based on the current data or expl...Loe edasi...
This book provides a conceptual introduction to regression analysis and machine learning and their applications in education research. It discusses their diverse applications, including its role in predicting future events based on the current dat...Loe edasi...
This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design of experiments, and related methods. For eas...Loe edasi...
This text presents selected applications of discrete-time stochastic processes that involve random interactions and algorithms, and revolve around the Markov property. It covers recurrence properties of (excited) random walks, convergence and mixi...Loe edasi...
Advancements in the technology and availability of data sources have led to the `Big Data era. Working with large data offers the potential to uncover more fine-grained patterns and take timely and accurate decisions, but it also creates a lot of...Loe edasi...
