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...
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...
This book illustrates different techniques and structures that are used in knowledge representation and machine learning. The aim of this book is to draw the attention of graduates, researchers and practitioners working in field of information techno...Loe edasi...
The book introduces phenomenal growth of data generated by increasing numbers of genome sequencing projects and other throughput technology-led experimental efforts. It provides information about various sources of gene expression data, and pre-pr...Loe edasi...
In a VUCA world, which is becoming increasingly volatile, uncertain, and complex, companies, organizations, and states must respond promptly and adequately to the respective situations. Making decisions based on past experiences is less successful...Loe edasi...
This presents recent advancements in probabilistic geotechnical site characterization. It reviews probability theories and models for cross correlation and spatial correlation, and presents methods for Bayesian parameter estimation and prediction....Loe edasi...
This book introduces the concept of “bespoke learning”, a new mechanistic approach that makes it possible to generate values of an output variable at each designated value of an associated input variable. Here the output variable generally provide...Loe edasi...
The surging predictive analytics market is expected to grow from 10.5 billion today to 28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predicti...Loe edasi...
