Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks (A Bradford Book)

$30.00 - $27.00

(as of Mar 28,2020 11:36:15 UTC – Details)



Artificial neural networks are nonlinear mapping systems whose structure is loosely based on principles observed in the nervous systems of humans and animals. The basic idea is that massive systems of simple units linked together in appropriate ways can generate many complex and interesting behaviors. This book focuses on the subset of feedforward artificial neural networks called multilayer perceptrons (MLP). These are the mostly widely used neural networks, with applications as diverse as finance (forecasting), manufacturing (process control), and science (speech and image recognition).

This book presents an extensive and practical overview of almost every aspect of MLP methodology, progressing from an initial discussion of what MLPs are and how they might be used to an in-depth examination of technical factors affecting performance. The book can be used as a tool kit by readers interested in applying networks to specific problems, yet it also presents theory and references outlining the last ten years of MLP research.





Advances in Data Mining and Modeling: Hong Kong 27 – 28 June 2002

$148.00 - $87.96

(as of Mar 28,2020 09:37:32 UTC – Details)



Data mining and data modeling are hot topics and are under fast development. Because of their wide applications and rich research contents, many practitioners and academics are attracted to work in these areas. With a view to promoting communication and collaboration among the practitioners and researchers in Hong Kong, a workshop on data mining and modeling was held in June 2002. Prof Ngaiming Mok, Director of the Institute of Mathematical Research, The University of Hong Kong, and Prof Tze Leung Lai (Stanford University), C V Starr Professor of the University of Hong Kong, initiated the workshop.This book contains selected papers presented at the workshop. The papers fall into two main categories: data mining and data modeling. Data mining papers deal with pattern discovery, clustering algorithms, classification and practical applications in the stock market. Data modeling papers treat neural network models, time series models, statistical models and practical applications.



Ford Pick-ups/Expedition and Lincoln Navigator, 1997-2009 (Chilton’s Total Car Care Repair Manual)

$35.50 - $44.90

(as of Mar 28,2020 07:38:44 UTC – Details)



Total Car Care is the most complete, step-by-step automotive repair manual you’ll ever use. All repair procedures are supported by detailed specifications, exploded views, and photographs. From the simplest repair procedure to the most complex, trust Chilton’s Total Car Care to give you everything you need to do the job. Save time and money by doing it yourself, with the confidence only a Chilton Repair Manual can provide.Used Book in Good Condition



The Medieval World (Routledge Worlds)

$72.95 - $52.46

(as of Mar 28,2020 05:43:23 UTC – Details)



Ranging from Connacht to Constantinople and from Tynemouth to Timbuktu, the forty-four contributors to The Medieval World seek to bring the Middle Ages to life, offering definitive appraisals of the distinctive features of the period.

This second edition includes six additional chapters, covering the Byzantine empire, illuminated manuscripts, the ‘ésprit laïque‘ of the late middle ages, saints and martyrs, the papal chancery and scholastic thought. Chapters are arranged thematically within four parts:

1. Identities, Selves and Others

2. Beliefs, Social Values and Symbolic Order

3. Power and Power Structures

4. Elites, Organisations and Groups

The Medieval World presents the reader with an authoritative account of original scholarship across the medieval millennium and provides essential reading for all students of the subject.





Big Data: Information in the Digital World with Science Activities for Kids (Build It Yourself)

00.00

(as of Mar 28,2020 04:09:27 UTC – Details)


What is big data and what does it have to do with you?

Have you watched videos online today? Did you post photographs on social media? Did you upload your English essay to Google docs?

All of these questions are questions about data. Data is information. It can be stored in books, magazines, on graph paper, in computers, and with many other methods. Most of the data that exists today is stored in computers, and the amount of data humans produce is doubling every year and half. That’s why it’s called big data!

In Big Data: Information in the Digital World with Science Activities for Kids, kids ages 10 to 15 explore the definition of data and learn about the relationship between data, computers, and people. They learn about the history of data, the transition from paper to computers, and the role that search engines such as Google play in handling data. Data management, data analytics, and the history of computers are all topics covered in this book on big numbers for kids.

Data is something computer scientists think about a lot. A computer’s capacity to function and perform is directly related to how much data it can store. A computer that can’t store much data won’t be very popular. As more and more of our daily lives become connected to computers—schoolwork, watching movies on a laptop, paying for snacks with a debit card—computers are required to handle more and more data. New improvements in data storage mean that there are fewer limits on the amount of data businesses can store, but what does that mean for users? How does data management make our lives easier? Do we need all of this information or are we storing data we’ll never use again simply because we can?

Throughout Big Data, STEAM investigations and experiments provide hands-on, problem-solving opportunities for students that incorporate various challenges and tools. Using readily available household items and recycled materials, each activity will take the reader through an inquiry-based, open-ended investigation that leaves plenty of room to explore individual creativity. With essential questions, fun facts, and links to online primary sources and videos, kids will mine the topic of big data and become better, more informed digital citizens of the world!



Java for Data Science

$49.99 - $43.99

(as of Mar 28,2020 02:15:51 UTC – Details)



Examine the techniques and Java tools supporting the growing field of data science About This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples Make your Java applications more capable using machine learning Who This Book Is For This book is for Java developers who are comfortable developing applications in Java. Those who now want to enter the world of data science or wish to build intelligent applications will find this book ideal. Aspiring data scientists will also find this book very helpful. What You Will Learn Understand the nature and key concepts used in the field of data science Grasp how data is collected, cleaned, and processed Become comfortable with key data analysis techniques See specialized analysis techniques centered on machine learning Master the effective visualization of your data Work with the Java APIs and techniques used to perform data analysis In Detail Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this book, we cover the important data science concepts and how they are supported by Java, as well as the often statistically challenging techniques, to provide you with an understanding of their purpose and application. The book starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. The next section examines the major categories of data analysis including text, visual, and audio data,



Knowledge Discovery for Counterterrorism and Law Enforcement (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

$115.00 - $33.52

(as of Mar 27,2020 22:57:36 UTC – Details)



Most of the research aimed at counterterrorism, fraud detection, or other forensic applications assumes that this is a specialized application domain for mainstream knowledge discovery. Unfortunately, knowledge discovery changes completely when the datasets being used have been manipulated in order to conceal some underlying activity. Knowledge Discovery for Counterterrorism and Law Enforcement operates from the premise that detection algorithms must be rethought to be effective in this domain, and presents a new approach based on cutting-edge analysis for use in adversarial settings.

Reveals How Criminals Conceal Information

 

This volume focuses on four main forms of knowledge discovery: prediction, clustering, relationship discovery, and textual analysis. For each of these application areas, the author discusses opportunities for concealment that are available to criminals and reveals some of the tactics that can aid in detecting them. He reviews what is known about the different technologies for each area and evaluates their effectiveness. The book also supplies a preview of technologies currently under development and describes how they will fit in to existing approaches to knowledge discovery.

Provides Proactive Formulas for Staying One Step Ahead of Adversaries

 

While all knowledge-discovery systems are susceptible to manipulation, designers and users of algorithmic systems who are armed with the knowledge of these subversive tactics are better able to create systems to avoid these vulnerabilities. This book delineates an effective process for integrating knowledge-discovery tools, provides a unique understanding of the limits of the technology, and contains a clear presentation of the upsides and pitfalls of data collection. It is a powerful weapon in the arsenal of anyone confronting the increasingly sophisticUsed Book in Good Condition



The Transformative Power of Mobile Medicine: Leveraging Innovation, Seizing Opportunities and Overcoming Obstacles of mHealth

$125.00 - $106.25

(as of Mar 27,2020 21:13:52 UTC – Details)


The Transformative Power of Mobile Medicine: Leveraging Innovation, Seizing Opportunities, and Overcoming Obstacles of mHealth addresses the rapid advances taking place in mHealth and their impact on clinicians and patients. It provides guidance on reliable mobile health apps that are based on sound scientific evidence, while also offering advice on how to stay clear of junk science. The book explores the latest developments, including the value of blockchain, the emerging growth of remote sensors in chronic patient care, the potential use of Amazon Alexa and Google Assistant as patient bedside assistants, the use of Amazon’s IoT button, and much more.

This book enables physicians and nurses to gain a deep understanding of the strengths and weaknesses of mobile health and helps them choose evidence-based mobile medicine tools to improve patient care.



Mining Software Specifications: Methodologies and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

$230.00 - $131.87

(as of Mar 27,2020 19:30:24 UTC – Details)



An emerging topic in software engineering and data mining, specification mining tackles software maintenance and reliability issues that cost economies billions of dollars each year. The first unified reference on the subject, Mining Software Specifications: Methodologies and Applications describes recent approaches for mining specifications of software systems. Experts in the field illustrate how to apply state-of-the-art data mining and machine learning techniques to address software engineering concerns.

In the first set of chapters, the book introduces a number of studies on mining finite state machines that employ techniques, such as grammar inference, partial order mining, source code model checking, abstract interpretation, and more. The remaining chapters present research on mining temporal rules/patterns, covering techniques that include path-aware static program analyses, lightweight rule/pattern mining, statistical analysis, and other interesting approaches. Throughout the book, the authors discuss how to employ dynamic analysis, static analysis, and combinations of both to mine software specifications.

According to the US National Institute of Standards and Technology in 2002, software bugs have cost the US economy 59.5 billion dollars a year. This volume shows how specification mining can help find bugs and improve program understanding, thereby reducing unnecessary financial losses. The book encourages the industry adoption of specification mining techniques and the assimilation of these techniques in standard integrated development environments (IDEs).