Learn Bootstrap The Collection

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Learn Bootstrap The Collection

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Author : Maria Antonietta Perna
language : en
Publisher: SitePoint Pty Ltd
Release Date : 2018-08-06

Learn Bootstrap The Collection written by Maria Antonietta Perna and has been published by SitePoint Pty Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-06 with Computers categories.

Bootstrap stands as the most popular open-source, front-end framework on the Web. Since its official release in 2011, it has undergone several changes, and it's now one of the most stable and responsive frameworks available. It's loved by web developers of all levels, as it gives them the capability to build a functional, attractive website design within minutes. A novice developer with just some basic knowledge of HTML and little CSS can easily get started with Bootstrap. This collection presents three books: Your First Week With Bootstrap, a collection of articles introducing Bootstrap 8 Practical Bootstrap Projects, which presents several complete, real world Bootrap projects Bootstrap: Related Tools & Skills, which contains a collection of articles outlining essential tools and skills that every Bootstrap developer should know. This collection is for all frontend developers who want to build responsive, mobile-first websites with Bootstrap. You'll need to be familiar with HTML and CSS and have a reasonable level of understanding of JavaScript in order to follow the discussion.

Statistical Machine Learning

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Author : Richard Golden
language : en
Publisher: CRC Press
Release Date : 2020-06-24

Statistical Machine Learning written by Richard Golden and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-24 with Computers categories.

The recent rapid growth in the variety and complexity of new machine learning architectures requires the development of improved methods for designing, analyzing, evaluating, and communicating machine learning technologies. Statistical Machine Learning: A Unified Framework provides students, engineers, and scientists with tools from mathematical statistics and nonlinear optimization theory to become experts in the field of machine learning. In particular, the material in this text directly supports the mathematical analysis and design of old, new, and not-yet-invented nonlinear high-dimensional machine learning algorithms. Features: Unified empirical risk minimization framework supports rigorous mathematical analyses of widely used supervised, unsupervised, and reinforcement machine learning algorithms Matrix calculus methods for supporting machine learning analysis and design applications Explicit conditions for ensuring convergence of adaptive, batch, minibatch, MCEM, and MCMC learning algorithms that minimize both unimodal and multimodal objective functions Explicit conditions for characterizing asymptotic properties of M-estimators and model selection criteria such as AIC and BIC in the presence of possible model misspecification This advanced text is suitable for graduate students or highly motivated undergraduate students in statistics, computer science, electrical engineering, and applied mathematics. The text is self-contained and only assumes knowledge of lower-division linear algebra and upper-division probability theory. Students, professional engineers, and multidisciplinary scientists possessing these minimal prerequisites will find this text challenging yet accessible. About the Author: Richard M. Golden (Ph.D., M.S.E.E., B.S.E.E.) is Professor of Cognitive Science and Participating Faculty Member in Electrical Engineering at the University of Texas at Dallas. Dr. Golden has published articles and given talks at scientific conferences on a wide range of topics in the fields of both statistics and machine learning over the past three decades. His long-term research interests include identifying conditions for the convergence of deterministic and stochastic machine learning algorithms and investigating estimation and inference in the presence of possibly misspecified probability models.

Bootstrap

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Author : Jake Spurlock
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-05-08

Bootstrap written by Jake Spurlock and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-08 with Computers categories.

Discover how easy it is to design killer interfaces and responsive websites with the Bootstrap framework. This practical book gets you started building pages with Bootstrap’s HTML/CSS-based tools and design templates right away. You’ll also learn how to extend your app with interactive features, using its suite of jQuery plugins—often without writing a single line of code. Developed by Twitter and available free from GitHub, Bootstrap supports responsive design by dynamically adjusting your web page layout. With just a basic knowledge of HTML, CSS, and JavaScript, you can build apps that work equally well on desktop screens, smartphones, and tablets. This book shows you how. Become familiar with Bootstrap’s file structure, grid systems, and container layouts Learn HTML elements for typography, code, tables, forms, buttons, images, and icons Design interfaces and other web elements, such as navigation, breadcrumbs, and custom modal windows Use jQuery plugins for features such as revolving slideshows, tabbable interfaces, and dropdown menus Modify everything from column count to typography colors with the LESS stylesheet language

Bootstrap Methods And Their Application

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Author : A. C. Davison
language : en
Publisher: Cambridge University Press
Release Date : 1997-10-28

Bootstrap Methods And Their Application written by A. C. Davison and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-10-28 with Computers categories.

Disk contains the library functions and documentation for use with Splus for Windows.

Machine Learning And Data Mining In Pattern Recognition

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Author : Petra Perner
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-08-12

Machine Learning And Data Mining In Pattern Recognition written by Petra Perner and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-12 with Computers categories.

This book constitutes the refereed proceedings of the 7th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2011, held in New York, NY, USA. The 44 revised full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized in topical sections on classification and decision theory, theory of learning, clustering, application in medicine, webmining and information mining; and machine learning and image mining.

Fundamentals And Methods Of Machine And Deep Learning

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Author : Pradeep Singh
language : en
Publisher: John Wiley & Sons
Release Date : 2022-03-02

Fundamentals And Methods Of Machine And Deep Learning written by Pradeep Singh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-02 with Computers categories.

FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING The book provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications. Over the past two decades, the field of machine learning and its subfield deep learning have played a main role in software applications development. Also, in recent research studies, they are regarded as one of the disruptive technologies that will transform our future life, business, and the global economy. The recent explosion of digital data in a wide variety of domains, including science, engineering, Internet of Things, biomedical, healthcare, and many business sectors, has declared the era of big data, which cannot be analysed by classical statistics but by the more modern, robust machine learning and deep learning techniques. Since machine learning learns from data rather than by programming hard-coded decision rules, an attempt is being made to use machine learning to make computers that are able to solve problems like human experts in the field. The goal of this book is to present a??practical approach by explaining the concepts of machine learning and deep learning algorithms with applications. Supervised machine learning algorithms, ensemble machine learning algorithms, feature selection, deep learning techniques, and their applications are discussed. Also included in the eighteen chapters is unique information which provides a clear understanding of concepts by using algorithms and case studies illustrated with applications of machine learning and deep learning in different domains, including disease prediction, software defect prediction, online television analysis, medical image processing, etc. Each of the chapters briefly described below provides both a chosen approach and its implementation. Audience Researchers and engineers in artificial intelligence, computer scientists as well as software developers.

Advances In Neural Networks Isnn 2006

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Author :
language : en
Publisher: Springer Science & Business Media
Release Date : 2006

Advances In Neural Networks Isnn 2006 written by and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Artificial intelligence categories.

Technology Enhanced Learning

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Author :
language : en
Publisher: BRILL
Release Date : 2010-01-01

Technology Enhanced Learning written by and has been published by BRILL this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-01-01 with Education categories.

Designing for technology enhanced learning (TEL) is often a demanding process. It involves creating challenging learning tasks, making sure that students have access to the right tools and resources, and ensuring there are appropriate opportunities for them to learn with and from each other. Good design is creative, and it also depends on deep experience, sound evidence about learning and an understanding of the capabilities of technology. This book introduces the use of design patterns and pattern languages as ways of capturing and sharing TEL design knowledge. The editors have assembled a team of authors who have pioneered research and development in this rapidly expanding field. The book surveys the state-of-the art and identifies productive lines for future research. It will be invaluable to researchers, teachers, students and professional TEL designers.

Nanoelectronics Circuits And Communication Systems

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Author : Vijay Nath
language : en
Publisher: Springer Nature
Release Date : 2020-11-17

Nanoelectronics Circuits And Communication Systems written by Vijay Nath and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-17 with Technology & Engineering categories.

This book features selected papers presented at the Fifth International Conference on Nanoelectronics, Circuits and Communication Systems (NCCS 2019). It covers a range of topics, including nanoelectronic devices, microelectronics devices, material science, machine learning, Internet of things, cloud computing, computing systems, wireless communication systems, advances in communication 5G and beyond. Further, it discusses VLSI circuits and systems, MEMS, IC design and testing, electronic system design and manufacturing, speech signal processing, digital signal processing, FPGA-based wireless communication systems and FPGA-based system design, Industry 4.0, e-farming, semiconductor memories, and IC fault detection and correction.

Optimization In Machine Learning And Applications

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Author : Anand J. Kulkarni
language : en
Publisher: Springer Nature
Release Date : 2019-11-29

Optimization In Machine Learning And Applications written by Anand J. Kulkarni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-29 with Technology & Engineering categories.

This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.