Deep Learning with Structured Data

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Publisher : Simon and Schuster
ISBN 13 : 163835717X
Total Pages : 262 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Deep Learning with Structured Data by : Mark Ryan

Download or read book Deep Learning with Structured Data written by Mark Ryan and published by Simon and Schuster. This book was released on 2020-12-08 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases. Summary Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world businesses depend on. Filled with practical, relevant applications, this book teaches you how deep learning can augment your existing machine learning and business intelligence systems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Here’s a dirty secret: Half of the time in most data science projects is spent cleaning and preparing data. But there’s a better way: Deep learning techniques optimized for tabular data and relational databases deliver insights and analysis without requiring intense feature engineering. Learn the skills to unlock deep learning performance with much less data filtering, validating, and scrubbing. About the book Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases. Get started using a dataset based on the Toronto transit system. As you work through the book, you’ll learn how easy it is to set up tabular data for deep learning, while solving crucial production concerns like deployment and performance monitoring. What's inside When and where to use deep learning The architecture of a Keras deep learning model Training, deploying, and maintaining models Measuring performance About the reader For readers with intermediate Python and machine learning skills. About the author Mark Ryan is a Data Science Manager at Intact Insurance. He holds a Master's degree in Computer Science from the University of Toronto. Table of Contents 1 Why deep learning with structured data? 2 Introduction to the example problem and Pandas dataframes 3 Preparing the data, part 1: Exploring and cleansing the data 4 Preparing the data, part 2: Transforming the data 5 Preparing and building the model 6 Training the model and running experiments 7 More experiments with the trained model 8 Deploying the model 9 Recommended next steps

Deep Learning

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Publisher : MIT Press
ISBN 13 : 0262337371
Total Pages : 801 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Deep Learning by : Ian Goodfellow

Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Neural Networks for Natural Language Processing

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Publisher : IGI Global
ISBN 13 : 1799811611
Total Pages : 227 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Neural Networks for Natural Language Processing by : S., Sumathi

Download or read book Neural Networks for Natural Language Processing written by S., Sumathi and published by IGI Global. This book was released on 2019-11-29 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information in today’s advancing world is rapidly expanding and becoming widely available. This eruption of data has made handling it a daunting and time-consuming task. Natural language processing (NLP) is a method that applies linguistics and algorithms to large amounts of this data to make it more valuable. NLP improves the interaction between humans and computers, yet there remains a lack of research that focuses on the practical implementations of this trending approach. Neural Networks for Natural Language Processing is a collection of innovative research on the methods and applications of linguistic information processing and its computational properties. This publication will support readers with performing sentence classification and language generation using neural networks, apply deep learning models to solve machine translation and conversation problems, and apply deep structured semantic models on information retrieval and natural language applications. While highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and development professionals, IT specialists, industrialists, technology developers, data analysts, data scientists, academics, researchers, and students seeking current research on the fundamental concepts and techniques of natural language processing.

The Universal Deep Structure of Modern Poetry

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Publisher : Cambridge Scholars Publishing
ISBN 13 : 1527549100
Total Pages : 255 pages
Book Rating : 4.5/5 (275 download)

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Book Synopsis The Universal Deep Structure of Modern Poetry by : John A.F. Hopkins

Download or read book The Universal Deep Structure of Modern Poetry written by John A.F. Hopkins and published by Cambridge Scholars Publishing. This book was released on 2020-04-02 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: With something of a poetry renaissance currently under way worldwide, there is now, more than ever, a need for a solidly-based methodology for interpreting poems: something more empirical than traditional ‘lit-crit’ approaches, and something more linguistically-informed than the version of ‘postmodernism’ rampant in certain Anglophone universities. The latter approach, which tends to allow the individual reader to do what he/she likes with a poetic text, is inadequate to interpret modernist poetry, whose English-language precursors may be found in the late Romantics; its pioneers were already writing (in France) as early as 1840. What is so different about the modernists? Most importantly, their works are monumental, in that they are strongly resistant to deconstruction. Contributing to this resistance is the fact that they are built around two deep-level propositions, each of which generates a set of indirectly-signifying images, sharing the same internal structure, but having a different vocabulary. Thus, they do not signify according to linear narrative, but according to these propositions—and the relation between them—which may be reconstructed by a careful comparison of images on the textual surface. Every text—as subject-sign—refers to an intertextual object-sign, which is usually another poem, but may also be a film or other form of art. Mediating between these two signs is their reader-constructed interpretant, which completes the semiotic triad. As this book shows, the novelty of this sign is thrown into relief by the contrast it makes with a lexical counterpart from the reader’s experience, which differs from the interpretant in structure. The book’s inclusion of French and Japanese, as well as English poems, shows that deep-level signifying mechanisms may well be universal, with considerable research and pedagogical implications.

Natural Language Processing

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Publisher : Cambridge University Press
ISBN 13 : 1108420214
Total Pages : 487 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Natural Language Processing by : Yue Zhang

Download or read book Natural Language Processing written by Yue Zhang and published by Cambridge University Press. This book was released on 2021-01-07 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.

Methods of Text and Discourse Analysis

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Publisher : SAGE
ISBN 13 : 9780761964834
Total Pages : 288 pages
Book Rating : 4.9/5 (648 download)

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Book Synopsis Methods of Text and Discourse Analysis by : Stefan Titscher

Download or read book Methods of Text and Discourse Analysis written by Stefan Titscher and published by SAGE. This book was released on 2000-07-28 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'This volume is the most comprehensive overview to date of sociologically orientated approaches to text and discourse analysis and is worth reading even for those who are interested only in purely linguistiv approaches to text and discourse. Its main merit, I think, is that it intorduces approaches which up to now have hardley been admitted into the universe of scientific discourse' - Discourse Studies Methods of Text and Discourse Analysis provides the most comprehensive overview currently available of linguistic and sociological approaches to text and discourse analysis. Among the 10 linguistic and sociological models surveyed in this book some of the more important are Grounded Theory, Content Analysis, Conversation Analysis and Critical Discourse Analysis. The book presents each approach according to a standardised format, which allows for direct systematic comparisons. The fully annotated lists of sources provide readers with an additional means of evaluation of the competing analytical methods. Interdisciplinary and international in its aims, Methods of Text and Discourse Analysis suggests the benefits both linguists and sociologists will derive from a more intimate knowledge of each others' methods and procedures.

Text Analytics with Python

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Publisher : Apress
ISBN 13 : 1484243544
Total Pages : 688 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Text Analytics with Python by : Dipanjan Sarkar

Download or read book Text Analytics with Python written by Dipanjan Sarkar and published by Apress. This book was released on 2019-05-21 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage Natural Language Processing (NLP) in Python and learn how to set up your own robust environment for performing text analytics. This second edition has gone through a major revamp and introduces several significant changes and new topics based on the recent trends in NLP. You’ll see how to use the latest state-of-the-art frameworks in NLP, coupled with machine learning and deep learning models for supervised sentiment analysis powered by Python to solve actual case studies. Start by reviewing Python for NLP fundamentals on strings and text data and move on to engineering representation methods for text data, including both traditional statistical models and newer deep learning-based embedding models. Improved techniques and new methods around parsing and processing text are discussed as well. Text summarization and topic models have been overhauled so the book showcases how to build, tune, and interpret topic models in the context of an interest dataset on NIPS conference papers. Additionally, the book covers text similarity techniques with a real-world example of movie recommenders, along with sentiment analysis using supervised and unsupervised techniques. There is also a chapter dedicated to semantic analysis where you’ll see how to build your own named entity recognition (NER) system from scratch. While the overall structure of the book remains the same, the entire code base, modules, and chapters has been updated to the latest Python 3.x release. What You'll Learn • Understand NLP and text syntax, semantics and structure• Discover text cleaning and feature engineering• Review text classification and text clustering • Assess text summarization and topic models• Study deep learning for NLP Who This Book Is For IT professionals, data analysts, developers, linguistic experts, data scientists and engineers and basically anyone with a keen interest in linguistics, analytics and generating insights from textual data.

Models of Thought

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Publisher : Yale University Press
ISBN 13 : 9780300024326
Total Pages : 550 pages
Book Rating : 4.0/5 (243 download)

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Book Synopsis Models of Thought by : Herbert Alexander Simon

Download or read book Models of Thought written by Herbert Alexander Simon and published by Yale University Press. This book was released on 1979-01-01 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nobel Laureate Herbert A. Simon has in the past quarter century been in the front line of the information-processing revolution; in fact, to a remarkable extent his and his colleagues' contributions have written the history of that revolution in cognitive psychology. Research in this burgeoning new branch of knowledge seeks to describe with precision the workings of the human mind in terms of a small number of basic mechanisms organized into strategies. Newly developed computer languages express theories of mental processes, so that computers can then simulate the predicted human behavior. This book brings together papers dating from the start of Simon's career to the present. Its focus is on modeling the chief components of human cognition and on testing these models experimentally. After considering basic structural elements of the human information-processing system (especially search, selective attention, and storage in memory), Simon builds from these components a system capable of solving problems, inducing rules and concepts, perceiving, and understanding. These essays describe a relatively austere, simple, and unified processing system capable of highly complex and various tasks. They provide strong evidence for an explanation of human thinking in terms of basic information processes.

Multimodal Scene Understanding

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Publisher : Academic Press
ISBN 13 : 0128173599
Total Pages : 424 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Multimodal Scene Understanding by : Michael Ying Yang

Download or read book Multimodal Scene Understanding written by Michael Ying Yang and published by Academic Press. This book was released on 2019-07-16 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. - Contains state-of-the-art developments on multi-modal computing - Shines a focus on algorithms and applications - Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning

Software Design – Cognitive Aspect

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Publisher : Springer Science & Business Media
ISBN 13 : 9781852332532
Total Pages : 164 pages
Book Rating : 4.3/5 (325 download)

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Book Synopsis Software Design – Cognitive Aspect by : Francoise Detienne

Download or read book Software Design – Cognitive Aspect written by Francoise Detienne and published by Springer Science & Business Media. This book was released on 2001-10-12 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering a variety of areas including software analysis, design, coding and maintenance, this text details the research conducted since the 1970s in this fast-developing field before going on to define a computer program from the viewpoint of computing and cognitive psychology. The two essential sides of programming, software production and software understanding, are given detailed treatment, with parallels drawn throughout between studies on processing texts written in natural language and processing computer programs. Of particular interest to researchers, practitioners and graduates in cognitive psychology, cognitive ergonomics and computer science.

Neural Network Methods in Natural Language Processing

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Publisher : Morgan & Claypool Publishers
ISBN 13 : 162705295X
Total Pages : 311 pages
Book Rating : 4.6/5 (27 download)

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Book Synopsis Neural Network Methods in Natural Language Processing by : Yoav Goldberg

Download or read book Neural Network Methods in Natural Language Processing written by Yoav Goldberg and published by Morgan & Claypool Publishers. This book was released on 2017-04-17 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries. The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.

Deep Learning for Robot Perception and Cognition

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Publisher : Academic Press
ISBN 13 : 0323885721
Total Pages : 638 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Deep Learning for Robot Perception and Cognition by : Alexandros Iosifidis

Download or read book Deep Learning for Robot Perception and Cognition written by Alexandros Iosifidis and published by Academic Press. This book was released on 2022-02-04 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. - Presents deep learning principles and methodologies - Explains the principles of applying end-to-end learning in robotics applications - Presents how to design and train deep learning models - Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more - Uses robotic simulation environments for training deep learning models - Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis

Mapping Strategic Thought

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Publisher :
ISBN 13 :
Total Pages : 452 pages
Book Rating : 4.:/5 (321 download)

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Book Synopsis Mapping Strategic Thought by : Anne Sigismund Huff

Download or read book Mapping Strategic Thought written by Anne Sigismund Huff and published by . This book was released on 1990-12-11 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: A two-fold cognitive study including a description of empirical investigations on issues of concern to strategic management, and a presentation of a set of methodological tools for depicting and analyzing managerial thought.

CIKM'13

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Publisher :
ISBN 13 : 9781450326964
Total Pages : 938 pages
Book Rating : 4.3/5 (269 download)

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Book Synopsis CIKM'13 by : CIKM 13 Conference Committee

Download or read book CIKM'13 written by CIKM 13 Conference Committee and published by . This book was released on 2013-10-27 with total page 938 pages. Available in PDF, EPUB and Kindle. Book excerpt: CIKM'13: 22nd ACM International Conference on Information and Knowledge Management Oct 27, 2013-Nov 01, 2013 San Francisco, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.

Interpretable Machine Learning

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Publisher : Lulu.com
ISBN 13 : 0244768528
Total Pages : 320 pages
Book Rating : 4.2/5 (447 download)

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Book Synopsis Interpretable Machine Learning by : Christoph Molnar

Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Understanding and Teaching Reading

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Publisher : Routledge
ISBN 13 : 1135438625
Total Pages : 535 pages
Book Rating : 4.1/5 (354 download)

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Book Synopsis Understanding and Teaching Reading by : Emerald Dechant

Download or read book Understanding and Teaching Reading written by Emerald Dechant and published by Routledge. This book was released on 2013-09-13 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the words of Aldous Huxley, "Every man who knows how to read has it in his power to magnify himself, to multiply the ways in which he exists, to make his life full, significant and interesting." Few people question the value of reading; in fact, most extol its virtues. As our culture becomes more complex, reading plays an increasingly greater role in satisfying personal needs and in promoting social awareness and growth. In the last 20 years, the teaching of this invaluable skill has focused so intensely on comprehension and prediction from context that it has lost sight of the significance of automaticity and fluency in the word-identification process. Reading is a synthesis of word recognition and comprehension; thus, this text is about these basic processes and their integration. A common plea from teachers today is that research and psychology be translated into teaching behavior. Therefore, the aim of this book is twofold: one, to identify, report, organize, and discuss those bits of data, research and theory that are most relevant to the teacher's understanding of the reading process; and two, to help educators to interpret and apply theory and research data to everyday classroom teaching, as well as to the problems encountered frequently in developmental and remedial teaching.

Cooperating with Written Texts

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Author :
Publisher : Walter de Gruyter
ISBN 13 : 9783110127232
Total Pages : 720 pages
Book Rating : 4.1/5 (272 download)

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Book Synopsis Cooperating with Written Texts by : Dieter Stein

Download or read book Cooperating with Written Texts written by Dieter Stein and published by Walter de Gruyter. This book was released on 1992 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: