Learning Processing

Author : Daniel Shiffman
Publisher : Newnes
Page : 564 pages
File Size : 48,5 Mb
Release : 2015-09-09
Category : Computers
ISBN : 9780123947925

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Learning Processing by Daniel Shiffman Pdf

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

Author : Allison Parrish,Ben Fry,Casey Reas
Publisher : Maker Media, Inc.
Page : 266 pages
File Size : 52,7 Mb
Release : 2016-05-11
Category : Computers
ISBN : 9781457186790

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Getting Started with Processing.py by Allison Parrish,Ben Fry,Casey Reas Pdf

Processing opened up the world of programming to artists, designers, educators, and beginners. The Processing.py Python implementation of Processing reinterprets it for today's web. This short book gently introduces the core concepts of computer programming and working with Processing. Written by the co-founders of the Processing project, Reas and Fry, along with co-author Allison Parrish, Getting Started with Processing.py is your fast track to using Python's Processing mode.

Author : Wan-Chi Siu,Lap-Pui Chau,Liang Wang,Tieniu Tang
Publisher : CRC Press
Page : 654 pages
File Size : 50,8 Mb
Release : 2018-12-07
Category : Computers
ISBN : 9780429592263

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Learning Approaches in Signal Processing by Wan-Chi Siu,Lap-Pui Chau,Liang Wang,Tieniu Tang Pdf

Coupled with machine learning, the use of signal processing techniques for big data analysis, Internet of things, smart cities, security, and bio-informatics applications has witnessed explosive growth. This has been made possible via fast algorithms on data, speech, image, and video processing with advanced GPU technology. This book presents an up-to-date tutorial and overview on learning technologies such as random forests, sparsity, and low-rank matrix estimation and cutting-edge visual/signal processing techniques, including face recognition, Kalman filtering, and multirate DSP. It discusses the applications that make use of deep learning, convolutional neural networks, random forests, etc. The applications include super-resolution imaging, fringe projection profilometry, human activities detection/capture, gesture recognition, spoken language processing, cooperative networks, bioinformatics, DNA, and healthcare.

Author : Cyril Goutte,Nicola Cancedda,Marc Dymetman,George Foster
Publisher : MIT Press
Page : 329 pages
File Size : 47,9 Mb
Release : 2009
Category : Computers
ISBN : 9780262072977

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Learning Machine Translation by Cyril Goutte,Nicola Cancedda,Marc Dymetman,George Foster Pdf

How Machine Learning can improve machine translation: enabling technologies and new statistical techniques.

Author : Ali N. Akansu,Sanjeev R. Kulkarni,Dmitry M. Malioutov
Publisher : John Wiley & Sons
Page : 312 pages
File Size : 45,7 Mb
Release : 2016-04-21
Category : Technology & Engineering
ISBN : 9781118745632

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Financial Signal Processing and Machine Learning by Ali N. Akansu,Sanjeev R. Kulkarni,Dmitry M. Malioutov Pdf

The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.

Author : Edith Kaan,Theres Grüter
Publisher : John Benjamins Publishing Company
Page : 250 pages
File Size : 40,6 Mb
Release : 2021-09-15
Category : Language Arts & Disciplines
ISBN : 9789027258946

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Prediction in Second Language Processing and Learning by Edith Kaan,Theres Grüter Pdf

There is ample evidence that language users, including second-language (L2) users, can predict upcoming information during listening and reading. Yet it is still unclear when, how, and why language users engage in prediction, and what the relation is between prediction and learning. This volume presents a collection of current research, insights, and directions regarding the role of prediction in L2 processing and learning. The contributions in this volume specifically address how different (L1-based) theoretical models of prediction apply to or may be expanded to account for L2 processing, report new insights on factors (linguistic, cognitive, social) that modulate L2 users’ engagement in prediction, and discuss the functions that prediction may or may not serve in L2 processing and learning. Taken together, this volume illustrates various fruitful approaches to investigating and accounting for differences in predictive processing within and across individuals, as well as across populations.

Author : Dan Jurafsky
Publisher : Pearson Education India
Page : 912 pages
File Size : 55,6 Mb
Release : 2000-09
Category : Electronic
ISBN : 8131716724

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Speech & Language Processing by Dan Jurafsky Pdf

Author : Nanning Zheng,Jianru Xue
Publisher : Springer Science & Business Media
Page : 371 pages
File Size : 40,5 Mb
Release : 2009-07-25
Category : Computers
ISBN : 9781848823129

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Statistical Learning and Pattern Analysis for Image and Video Processing by Nanning Zheng,Jianru Xue Pdf

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.

Author : Sk Md Obaidullah,KC Santosh,Teresa Goncalves,Nibaran Das,Kaushik Roy
Publisher : CRC Press
Page : 148 pages
File Size : 53,6 Mb
Release : 2019-11-25
Category : Computers
ISBN : 9781000739831

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Document Processing Using Machine Learning by Sk Md Obaidullah,KC Santosh,Teresa Goncalves,Nibaran Das,Kaushik Roy Pdf

Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document image analysis (DIA) domain using machine learning since it covers multiple document processing problems. Starting with an explanation of how Artificial Intelligence (AI) plays an important role in this domain, the book further discusses how different machine learning algorithms can be applied for classification/recognition and clustering problems regardless the type of input data: images or text. In brief, the book offers comprehensive coverage of the most essential topics, including: · The role of AI for document image analysis · Optical character recognition · Machine learning algorithms for document analysis · Extreme learning machines and their applications · Mathematical foundation for Web text document analysis · Social media data analysis · Modalities for document dataset generation This book serves both undergraduate and graduate scholars in Computer Science/Information Technology/Electrical and Computer Engineering. Further, it is a great fit for early career research scientists and industrialists in the domain.

Author : Stephan Raaijmakers
Publisher : Simon and Schuster
Page : 294 pages
File Size : 51,8 Mb
Release : 2022-12-20
Category : Computers
ISBN : 9781638353997

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Deep Learning for Natural Language Processing by Stephan Raaijmakers Pdf

Explore the most challenging issues of natural language processing, and learn how to solve them with cutting-edge deep learning! Inside Deep Learning for Natural Language Processing you’ll find a wealth of NLP insights, including: An overview of NLP and deep learning One-hot text representations Word embeddings Models for textual similarity Sequential NLP Semantic role labeling Deep memory-based NLP Linguistic structure Hyperparameters for deep NLP Deep learning has advanced natural language processing to exciting new levels and powerful new applications! For the first time, computer systems can achieve "human" levels of summarizing, making connections, and other tasks that require comprehension and context. Deep Learning for Natural Language Processing reveals the groundbreaking techniques that make these innovations possible. Stephan Raaijmakers distills his extensive knowledge into useful best practices, real-world applications, and the inner workings of top NLP algorithms. About the technology Deep learning has transformed the field of natural language processing. Neural networks recognize not just words and phrases, but also patterns. Models infer meaning from context, and determine emotional tone. Powerful deep learning-based NLP models open up a goldmine of potential uses. About the book Deep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library. You’ll learn to use state-of the-art tools and techniques including BERT and XLNET, multitask learning, and deep memory-based NLP. Fascinating examples give you hands-on experience with a variety of real world NLP applications. Plus, the detailed code discussions show you exactly how to adapt each example to your own uses! What's inside Improve question answering with sequential NLP Boost performance with linguistic multitask learning Accurately interpret linguistic structure Master multiple word embedding techniques About the reader For readers with intermediate Python skills and a general knowledge of NLP. No experience with deep learning is required. About the author Stephan Raaijmakers is professor of Communicative AI at Leiden University and a senior scientist at The Netherlands Organization for Applied Scientific Research (TNO). Table of Contents PART 1 INTRODUCTION 1 Deep learning for NLP 2 Deep learning and language: The basics 3 Text embeddings PART 2 DEEP NLP 4 Textual similarity 5 Sequential NLP 6 Episodic memory for NLP PART 3 ADVANCED TOPICS 7 Attention 8 Multitask learning 9 Transformers 10 Applications of Transformers: Hands-on with BERT

Author : Yue Zhang,Zhiyang Teng
Publisher : Cambridge University Press
Page : 487 pages
File Size : 53,9 Mb
Release : 2021-01-07
Category : Computers
ISBN : 9781108420211

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Natural Language Processing by Yue Zhang,Zhiyang Teng Pdf

This undergraduate textbook introduces essential machine learning concepts in NLP in a unified and gentle mathematical framework.

Author : Doris A. Graber
Publisher : University of Chicago Press
Page : 232 pages
File Size : 46,7 Mb
Release : 2012-07-15
Category : Political Science
ISBN : 9780226924762

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Processing Politics by Doris A. Graber Pdf

How often do we hear that Americans are so ignorant about politics that their civic competence is impaired, and that the media are to blame because they do a dismal job of informing the public? Processing Politics shows that average Americans are far smarter than the critics believe. Integrating a broad range of current research on how people learn (from political science, social psychology, communication, physiology, and artificial intelligence), Doris Graber shows that televised presentations—at their best—actually excel at transmitting information and facilitating learning. She critiques current political offerings in terms of their compatibility with our learning capacities and interests, and she considers the obstacles, both economic and political, that affect the content we receive on the air, on cable, or on the Internet. More and more people rely on information from television and the Internet to make important decisions. Processing Politics offers a sound, well-researched defense of these remarkably versatile media, and challenges us to make them work for us in our democracy.

Author : Delip Rao,Brian McMahan
Publisher : O'Reilly Media
Page : 256 pages
File Size : 52,8 Mb
Release : 2019-01-22
Category : Computers
ISBN : 9781491978207

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Natural Language Processing with PyTorch by Delip Rao,Brian McMahan Pdf

Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If you’re a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations. Explore computational graphs and the supervised learning paradigm Master the basics of the PyTorch optimized tensor manipulation library Get an overview of traditional NLP concepts and methods Learn the basic ideas involved in building neural networks Use embeddings to represent words, sentences, documents, and other features Explore sequence prediction and generate sequence-to-sequence models Learn design patterns for building production NLP systems

Author : Stefan Th. Gries,Dagmar Divjak
Publisher : Walter de Gruyter
Page : 250 pages
File Size : 50,9 Mb
Release : 2012-08-31
Category : Language Arts & Disciplines
ISBN : 9783110274059

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Frequency Effects in Language Learning and Processing by Stefan Th. Gries,Dagmar Divjak Pdf

The volume contains a collection of studies on how the analysis of corpus and psycholinguistic data reveal how linguistic knowledge is affected by the frequency of linguistic elements/stimuli. The studies explore a wide range of phenomena , from phonological reduction processes and palatalization to morphological productivity, diachronic change, adjective preposition constructions, auxiliary omission, and multi-word units. The languages studied are Spanish and artificial languages, Russian, Dutch, and English. The sister volume focuses on language representation.

Author : Linda Lamb,Arnold Robbins
Publisher : "O'Reilly Media, Inc."
Page : 356 pages
File Size : 52,9 Mb
Release : 1998
Category : Computers
ISBN : 1565924266

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Learning the Vi Editor by Linda Lamb,Arnold Robbins Pdf

For many users, working in the Unix environment means usingvi, a full-screen text editor available on most Unix systems. Even those who knowvioften make use of only a small number of its features. Learning the vi Editoris a complete guide to text editing withvi. Topics new to the sixth edition include multiscreen editing and coverage of fourviclones:vim,elvis,nvi, andvileand their enhancements tovi, such as multi-window editing, GUI interfaces, extended regular expressions, and enhancements for programmers. A new appendix describesvi's place in the Unix and Internet cultures. Quickly learn the basics of editing, cursor movement, and global search and replacement. Then take advantage of the more subtle power ofvi. Extend your editing skills by learning to useex, a powerful line editor, from withinvi. For easy reference, the sixth edition also includes a command summary at the end of each appropriate chapter. Topics covered include: Basic editing Moving around in a hurry Beyond the basics Greater power withex Global search and replacement Customizingviandex Command shortcuts Introduction to theviclones' extensions Thenvi,elvis,vim, andvileeditors Quick reference toviandexcommands viand the Internet