This book explores the development, trends and research of library and information sciences (LIS) in the digital age. Inside, readers will find research and case studies written by LIS experts, educators and theorists, most of whom have visited China, delivered presentations there and drafted their articles based on feedback they received. As a res...
This book presents the VISCERAL project benchmarks for analysis and retrieval of 3D medical images (CT and MRI) on a large scale, which used an innovative cloud-based evaluation approach where the image data were stored centrally on a cloud infrastructure and participants placed their programs in virtual machines on the cloud. The book presents the...
Neo4j is the world's leading graph database and offers users a radical new way of dealing with connected data. This book has been created to help you get to grips with it, providing you with an accessible route through a tool built to contend with the complexity of modern data. Learn the fundamental concepts behind Neo4j, and put them into pra...
Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide, developers and data scientists will discover how graph analytics deliver value, whether they're used for building dynamic network models or forecasting real-world ...
This open access handbook provides the first comprehensive overview of biometrics exploiting the shape of human blood vessels for biometric recognition, i.e. vascular biometrics, including finger vein recognition, hand/palm vein recognition, retina recognition, and sclera recognition. After an introductory chapter summarizing the state of the art i...
This free book brings together a set of original studies that use cutting-edge computational methods to investigate conflict at various geographic scales and degrees of intensity and violence. Methodologically, this book covers a variety of computational approaches from text mining and machine learning to agent-based modelling and social network an...
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature i...
This book offers an easily accessible and comprehensive guide to the entire market research process, from asking market research questions to collecting and analyzing data by means of quantitative methods. It is intended for all readers who wish to know more about the market research process, data management, and the most commonly used methods in m...
The revised 2nd edition of this book provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribut...
This book is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning.With careful treatment of topics that fill the curricular needs for the course, Probab...
Support Vector Machines (SVMs) are some of the most performant off-the-shelf, supervised machine-learning algorithms. In Support Vector Machines Succinctly, author Alexandre Kowalczyk guides readers through the building blocks of SVMs, from basic concepts to crucial problem-solving algorithms. He also includes numerous code examples and a lengthy b...
The demand for skilled data science practitioners in industry, academia, and government is rapidly growing. This book introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression and machine learning. It also helps you develop skills such a...
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data...
This open methodological book summarises existing analysing techniques using data from PIAAC, a study initiated by the OECD that assesses key cognitive and occupational skills of the adult population in more than 40 countries. The approximately 65 PIAAC datasets that has been published worldwide to date has been widely received and used by an inter...
Even as spending on digital transformation continues to skyrocket, mainframes nevertheless have major advantages for global enterprises. These systems still process huge amounts of information and allow for highly secure transactions. In this practical book, author Tom Taulli shows software developers how to pursue a hybrid approach by integrating ...
This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and princ...
Many forces affect software today: larger datasets, geographical disparities, complex company structures, and the growing need to be fast and nimble in the face of change. Proven approaches such as service-oriented and event-driven architectures are joined by newer techniques such as microservices, reactive architectures, DevOps, and stream process...
This open book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients.
Diagnostic and therapeutic technologies continue ...
In the light of better and more detailed administrative databases, this book provides statistical tools for evaluating the effects of public policies advocated by governments and public institutions. Experts from academia, national statistics offices and various research centers present modern econometric methods for an efficient data-driven policy...
This book provides a unique study of the complexities and consequences of irregular legal status of Senegalese migrants in Europe. It employs sophisticated quantitative methods to analyze unique life-history data to produce policy-relevant conclusions. Using the MAFE dataset as empirical evidence, the book focuses on the legal paths of Senegalese ...
This book provides an exhaustive picture of the role that annulment conflicts play in the EU multilevel system. Based on a rich dataset of annulment actions since the 1960s and a number of in-depth case studies, it explores the political dimension of annulment litigation, which has become an increasingly relevant judicial tool in the struggle over ...
Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, ...
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be...
This book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using tec...
This book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created ...
Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, cla...
This free book tells the story of how Sweden is becoming a virtually cashless society. Its goal is to improve readers' understanding of what is driving this transition, and of the factors that are fostering and hampering it. In doing so, the book covers the role of central banks, political factors, needs for innovation, and the stakeholders in...
You're sitting on a pile of interesting data. How do you transform that into money? It's easy to focus on the contents of the data itself, and to succumb to the (rather unimaginative) idea of simply collecting and reselling it in raw form. While that's certainly profitable right now, you'd do well to explore other opportunities ...
We've all heard it: according to Hal Varian, statistics is the next sexy job. Five years ago, in What is Web 2.0, Tim O'Reilly said that "data is the next Intel Inside." But what does that statement mean? Why do we suddenly care about statistics and about data? This report examines the many sides of data science - the technologi...
If you know how to program with Python and also know a little about probability, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math o...
Discover how graph databases can help you manage and query highly connected data. With this practical book, you'll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your ...
For the right use case, relational databases are powerful tools.
But today's users are asking for more than an RDBMS can handle. More features, more data, more speed and - most importantly - more connections.
This ebook introduces you - the RDBMS developer - to a new technology that leverages data connections like never before: the graph...