learning processing

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Learning Processing

Author : Daniel Shiffman
ISBN : 9780123947925
Genre : Computers
File Size : 54. 20 MB
Format : PDF, ePub
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Learning Processing, Second Edition, is a friendly start-up guide to Processing, a free, open-source alternative to expensive software and daunting programming languages. Requiring no previous experience, this book is for the true programming beginner. It teaches the basic building blocks of programming needed to create cutting-edge graphics applications including interactive art, live video processing, and data visualization. Step-by-step examples, thorough explanations, hands-on exercises, and sample code, supports your learning curve. A unique lab-style manual, the book gives graphic and web designers, artists, and illustrators of all stripes a jumpstart on working with the Processing programming environment by providing instruction on the basic principles of the language, followed by careful explanations of select advanced techniques. The book has been developed with a supportive learning experience at its core. From algorithms and data mining to rendering and debugging, it teaches object-oriented programming from the ground up within the fascinating context of interactive visual media. This book is ideal for graphic designers and visual artists without programming background who want to learn programming. It will also appeal to students taking college and graduate courses in interactive media or visual computing, and for self-study. A friendly start-up guide to Processing, a free, open-source alternative to expensive software and daunting programming languages No previous experience required—this book is for the true programming beginner! Step-by-step examples, thorough explanations, hands-on exercises, and sample code supports your learning curve

Information Processing In Motor Control And Learning

Author : George E. Stelmach
ISBN : 9781483268521
Genre : Psychology
File Size : 62. 67 MB
Format : PDF
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Information Processing in Motor Control and Learning provides the theoretical ideas and experimental findings in the field of motor behavior research. The text presents a balanced combination of theory and empirical data. Chapters discuss several theoretical issues surrounding skill acquisition; motor programming; and the nature and significance of preparation, rapid movement sequences, attentional demands, and sensorimotor integration in voluntary movements. The book will be interesting to psychologists, neurophysiologists, and graduate students in related fields.

Processing Analyzing And Learning Of Images Shapes And Forms

Author :
ISBN : 9780444642066
Genre : Mathematics
File Size : 25. 5 MB
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Processing, Analyzing and Learning of Images, Shapes, and Forms: Volume 19, Part One provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms. It covers mathematical models as well as fast computational techniques, and includes new chapters on Alternating diffusion: a geometric approach for sensor fusion, Shape Correspondence and Functional Maps, Geometric models for perception-based image processing, Decomposition schemes for nonconvex composite minimization: theory and applications, Low rank matrix recovery: algorithms and theory, Geometry and learning for deformation shape correspondence, and Factoring scene layout from monocular images in presence of occlusion. Presents a contemporary view on the topic, comprehensively covering the newest developments and content Provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms

Connectionist Statistical And Symbolic Approaches To Learning For Natural Language Processing

Author : Stefan Wermter
ISBN : 3540609253
Genre : Computers
File Size : 32. 78 MB
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This book is based on the workshop on New Approaches to Learning for Natural Language Processing, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. Most of the 32 papers included in the book are revised selected workshop presentations; some papers were individually solicited from members of the workshop program committee to give the book an overall completeness. Also included, and written with the novice reader in mind, is a comprehensive introductory survey by the volume editors. The volume presents the state of the art in the most promising current approaches to learning for NLP and is thus compulsory reading for researchers in the field or for anyone applying the new techniques to challenging real-world NLP problems.

Deep Learning For Natural Language Processing

Author : Palash Goyal
ISBN : 9781484236857
Genre : Computers
File Size : 76. 47 MB
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Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models. You’ll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP with practical examples. The first three chapters of the book cover the basics of NLP, starting with word-vector representation before moving onto advanced algorithms. The final chapters focus entirely on implementation, and deal with sophisticated architectures such as RNN, LSTM, and Seq2seq, using Python tools: TensorFlow, and Keras. Deep Learning for Natural Language Processing follows a progressive approach and combines all the knowledge you have gained to build a question-answer chatbot system. This book is a good starting point for people who want to get started in deep learning for NLP. All the code presented in the book will be available in the form of IPython notebooks and scripts, which allow you to try out the examples and extend them in interesting ways. What You Will Learn Gain the fundamentals of deep learning and its mathematical prerequisites Discover deep learning frameworks in Python Develop a chatbot Implement a research paper on sentiment classification Who This Book Is For Software developers who are curious to try out deep learning with NLP.

Learning Processing

Author : Daniel Shiffman
ISBN : 0123944430
Genre : Computers
File Size : 85. 68 MB
Format : PDF, ePub, Docs
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This book teaches you the basic building blocks of programming needed to create cutting-edge graphics applications including interactive art, live video processing, and data visualization. A unique lab-style manual, the book gives graphic and web designers, artists, and illustrators of all stripes a jumpstart on working with the Processing programming environment by providing instruction on the basic principles of the language, followed by careful explanations of select advanced techniques. Within these pages, ITP (Tisch School of the Arts, New York University) professor Daniel Shiffman demonstrates the fundamentals of programming that will expand your understanding of what is possible in the world of computer graphics. By travelling beyond the confines of proprietary software, you will be empowered to create your own custom design tools. * A friendly start-up guide to Processing, the free, open-source alternative to expensive software and daunting programming languages for the visual artist * No previous experience required-this book is for the true programming beginner! * Step-by-step examples, thorough explanations, hands-on exercises, and simple code samples support your learning curve. Source code and supplemental tutorials are also available through an online companion site

Economic Development As A Learning Process

Author : Franco Malerba
ISBN : 9780857937896
Genre : Business & Economics
File Size : 83. 61 MB
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Until recently, economists studying economic development have tended to consider it as a universal process, or focussed their attention on common aspects. This book originates from the growing recognition of significant sectoral differences in economic development and examines the catching-up process in five different economic sectors: pharmaceuticals, telecommunications equipment, semiconductors, software, and agro-food industries. Each of these sector studies explore the learning and catch-up processes in various developing countries, in order to identify both the common features, and those which differ significantly across sectors and nations. The authors pay particular attention to China, India, Brazil, Korea and Taiwan. Edited by two of the leading scholars in the field, this book will prove to be invaluable for academics and postgraduate students interested in economic and technological development, and evolutionary economics.

Statistical Learning And Pattern Analysis For Image And Video Processing

Author : Nanning Zheng
ISBN : 9781848823129
Genre : Computers
File Size : 55. 58 MB
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Why are We Writing This Book? Visual data (graphical, image, video, and visualized data) affect every aspect of modern society. The cheap collection, storage, and transmission of vast amounts of visual data have revolutionized the practice of science, technology, and business. Innovations from various disciplines have been developed and applied to the task of designing intelligent machines that can automatically detect and exploit useful regularities (patterns) in visual data. One such approach to machine intelligence is statistical learning and pattern analysis for visual data. Over the past two decades, rapid advances have been made throughout the ?eld of visual pattern analysis. Some fundamental problems, including perceptual gro- ing,imagesegmentation, stereomatching, objectdetectionandrecognition,and- tion analysis and visual tracking, have become hot research topics and test beds in multiple areas of specialization, including mathematics, neuron-biometry, and c- nition. A great diversity of models and algorithms stemming from these disciplines has been proposed. To address the issues of ill-posed problems and uncertainties in visual pattern modeling and computing, researchers have developed rich toolkits based on pattern analysis theory, harmonic analysis and partial differential eq- tions, geometry and group theory, graph matching, and graph grammars. Among these technologies involved in intelligent visual information processing, statistical learning and pattern analysis is undoubtedly the most popular and imp- tant approach, and it is also one of the most rapidly developing ?elds, with many achievements in recent years. Above all, it provides a unifying theoretical fra- work for intelligent visual information processing applications.

Vocabulary Learning Strategies And Foreign Language Acquisition

Author : Višnja Pavičić Takač
ISBN : 9781847690388
Genre : Language Arts & Disciplines
File Size : 50. 11 MB
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The book discusses vocabulary learning strategies as an integral subgroup of language learning strategies. It defines language learning strategies in general and their features on the basis of cognitive theory and relevant models of second language acquisition as the basis for empirical research. Furthermore, the book gives a survey of research on vocabulary learning strategies and describes three original empirical studies. Thus, the book attempts at integrating the approaches of theories of second language acquisition, the theory and practice of instructed foreign language learning, and the findings of current empirical research.

Learning To Rank For Information Retrieval And Natural Language Processing

Author : Hang Li
ISBN : 9781627055857
Genre : Computers
File Size : 32. 74 MB
Format : PDF, ePub, Mobi
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Learning to rank refers to machine learning techniques for training a model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on its problems recently, and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, major approaches, theories, applications, and future work. The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as two basic ranking tasks, namely ranking creation (or simply ranking) and ranking aggregation. In ranking creation, given a request, one wants to generate a ranking list of offerings based on the features derived from the request and the offerings. In ranking aggregation, given a request, as well as a number of ranking lists of offerings, one wants to generate a new ranking list of the offerings. Ranking creation (or ranking) is the major problem in learning to rank. It is usually formalized as a supervised learning task. The author gives detailed explanations on learning for ranking creation and ranking aggregation, including training and testing, evaluation, feature creation, and major approaches. Many methods have been proposed for ranking creation. The methods can be categorized as the pointwise, pairwise, and listwise approaches according to the loss functions they employ. They can also be categorized according to the techniques they employ, such as the SVM based, Boosting based, and Neural Network based approaches. The author also introduces some popular learning to rank methods in details. These include: PRank, OC SVM, McRank, Ranking SVM, IR SVM, GBRank, RankNet, ListNet & ListMLE, AdaRank, SVM MAP, SoftRank, LambdaRank, LambdaMART, Borda Count, Markov Chain, and CRanking. The author explains several example applications of learning to rank including web search, collaborative filtering, definition search, keyphrase extraction, query dependent summarization, and re-ranking in machine translation. A formulation of learning for ranking creation is given in the statistical learning framework. Ongoing and future research directions for learning to rank are also discussed. Table of Contents: Learning to Rank / Learning for Ranking Creation / Learning for Ranking Aggregation / Methods of Learning to Rank / Applications of Learning to Rank / Theory of Learning to Rank / Ongoing and Future Work

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