Author: Daniel Shiffman
Publisher: Newnes
ISBN: 0123947928
Category : Computers
Languages : en
Pages : 564

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Book Description
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
Publisher: Maker Media, Inc.
ISBN: 1457186799
Category : Computers
Languages : en
Pages : 266

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Book Description
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: Cyril Goutte
Publisher: MIT Press
ISBN: 0262072971
Category : Computers
Languages : en
Pages : 329

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

Author: Wan-Chi Siu
Publisher: CRC Press
ISBN: 0429592264
Category : Computers
Languages : en
Pages : 654

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Book Description
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: John L. Luckner
Publisher: Kendall/Hunt Publishing Company
ISBN: 9780787210007
Category : Active learning
Languages : en
Pages : 0

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Book Description

Author: M.A. Jabbar
Publisher: CRC Press
ISBN: 1000794741
Category : Computers
Languages : en
Pages : 257

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Book Description
The signal processing (SP) landscape has been enriched by recent advances in artificial intelligence (AI) and machine learning (ML), yielding new tools for signal estimation, classification, prediction, and manipulation. Layered signal representations, nonlinear function approximation and nonlinear signal prediction are now feasible at very large scale in both dimensionality and data size. These are leading to significant performance gains in a variety of long-standing problem domains like speech and Image analysis. As well as providing the ability to construct new classes of nonlinear functions (e.g., fusion, nonlinear filtering). This book will help academics, researchers, developers, graduate and undergraduate students to comprehend complex SP data across a wide range of topical application areas such as social multimedia data collected from social media networks, medical imaging data, data from Covid tests etc. This book focuses on AI utilization in the speech, image, communications and yirtual reality domains.

Author: Doris A. Graber
Publisher: University of Chicago Press
ISBN: 0226924769
Category : Political Science
Languages : en
Pages : 232

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Book Description
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: Li Deng
Publisher: Springer
ISBN: 9811052093
Category : Computers
Languages : en
Pages : 329

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Book Description
In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.

Author: Joellen Killion
Publisher:
ISBN: 9780990315896
Category : Feedback (Psychology)
Languages : en
Pages : 137

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Book Description

Author: Karthiek Reddy Bokka
Publisher: Packt Publishing Ltd
ISBN: 1838553673
Category : Computers
Languages : en
Pages : 372

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Book Description
Gain the knowledge of various deep neural network architectures and their application areas to conquer your NLP issues. Key FeaturesGain insights into the basic building blocks of natural language processingLearn how to select the best deep neural network to solve your NLP problemsExplore convolutional and recurrent neural networks and long short-term memory networksBook Description Applying deep learning approaches to various NLP tasks can take your computational algorithms to a completely new level in terms of speed and accuracy. Deep Learning for Natural Language Processing starts off by highlighting the basic building blocks of the natural language processing domain. The book goes on to introduce the problems that you can solve using state-of-the-art neural network models. After this, delving into the various neural network architectures and their specific areas of application will help you to understand how to select the best model to suit your needs. As you advance through this deep learning book, you’ll study convolutional, recurrent, and recursive neural networks, in addition to covering long short-term memory networks (LSTM). Understanding these networks will help you to implement their models using Keras. In the later chapters, you will be able to develop a trigger word detection application using NLP techniques such as attention model and beam search. By the end of this book, you will not only have sound knowledge of natural language processing but also be able to select the best text pre-processing and neural network models to solve a number of NLP issues. What you will learnUnderstand various pre-processing techniques for deep learning problemsBuild a vector representation of text using word2vec and GloVeCreate a named entity recognizer and parts-of-speech tagger with Apache OpenNLPBuild a machine translation model in KerasDevelop a text generation application using LSTMBuild a trigger word detection application using an attention modelWho this book is for If you’re an aspiring data scientist looking for an introduction to deep learning in the NLP domain, this is just the book for you. Strong working knowledge of Python, linear algebra, and machine learning is a must.