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  • 1
    Online Resource
    Online Resource
    Learning Java functional programming : create robust and maintainable Java applications using the functional style of programming (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785289354 , 1785289357
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Community experience distilled
    Keywords: Java (Computer program language) ; Functional programming (Computer science) ; Application software ; Programming ; Electronic books ; Electronic books ; local
    Abstract: Create robust and maintainable Java applications using the functional style of programming About This Book Explore how you can blend object-oriented and functional programming styles in Java Use lambda expressions to write flexible and succinct code A tutorial that strengthens your fundamentals in functional programming techniques to enhance your applications Who This Book Is For If you are a Java developer with object-oriented experience and want to use a functional programming approach in your applications, then this book is for you. All you need to get started is familiarity with basic Java object-oriented programming concepts. What You Will Learn Use lambda expressions to simplyfy code Use function composition to achieve code fluency Apply streams to simply implementations and achieve parallelism Incorporate recursion to support an application's functionality Provide more robust implementations using Optionals Implement design patterns with less code Refactor object-oriented code to create a functional solution Use debugging and testing techniques specific to functional programs In Detail Functional programming is an increasingly popular technology that allows you to simplify many tasks that are often cumbersome and awkward using an object-oriented approach. It is important to understand this approach and know how and when to apply it. Functional programming requires a different mindset, but once mastered it can be very rewarding. This book simplifies the learning process as a problem is described followed by its implementation using an object-oriented approach and then a solution is provided using appropriate functional programming techniques. Writing succinct and maintainable code is facilitated by many functional programming techniques including lambda expressions and streams. In this book, you will see numerous examples of how these techniques can be applied starting with an introduction to lambda expressions. Next, you will see how they can replace older approaches and be combined to achieve surprisingly elegant solutions to problems. This is followed by the investigation of related concepts such as the Optional class and monads, which offer an additional approach to handle problems. Design patterns have been instrumental in solving common problems. You will learn how these are enhanced with functional techniques. To transition from an object-oriented approach to a functional one, it is useful to have IDE support. IDE tools to refacto...
    Note: Includes index. - Description based on online resource; title from cover page (Safari, viewed November 30, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781783558483/?ar
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    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    Java for data science : examine the techniques and Java tools supporting the growing field of data science (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785281242 , 1785281240
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Java (Computer program language) ; Machine learning ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Examine the techniques and Java tools supporting the growing field of data science About This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples Make your Java applications more capable using machine learning Who This Book Is For This book is for Java developers who are comfortable developing applications in Java. Those who now want to enter the world of data science or wish to build intelligent applications will find this book ideal. Aspiring data scientists will also find this book very helpful. What You Will Learn Understand the nature and key concepts used in the field of data science Grasp how data is collected, cleaned, and processed Become comfortable with key data analysis techniques See specialized analysis techniques centered on machine learning Master the effective visualization of your data Work with the Java APIs and techniques used to perform data analysis In Detail Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this book, we cover the important data science concepts and how they are supported by Java, as well as the often statistically challenging techniques, to provide you with an understanding of their purpose and application. The book starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. The next section examines the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation. The final chapter illustrates an in-depth data science problem and provides a comprehensive, Java-based solution. Due to the nature of the topic, simple examples of techniques are presented early followed by a more detailed treatment later in the book. This permits a more natural introduction to the techniques and concepts presented in the book. Style and approach This book follows a tutorial approach, providing examples of each of the major concepts covered. With a...
    Note: Description based on online resource; title from cover (Safari, viewed January 27, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781785280115/?ar
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    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Natural language processing with Java : techniques for building machine learning and neural network models for NLP (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788993067 , 1788993063
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Natural language processing (Computer science) ; Java (Computer program language) ; Machine learning ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Explore various approaches to organize and extract useful text from unstructured data using Java Key Features Use deep learning and NLP techniques in Java to discover hidden insights in text Work with popular Java libraries such as CoreNLP, OpenNLP, and Mallet Explore machine translation, identifying parts of speech, and topic modeling Book Description Natural Language Processing (NLP) allows you to take any sentence and identify patterns, special names, company names, and more. The second edition of Natural Language Processing with Java teaches you how to perform language analysis with the help of Java libraries, while constantly gaining insights from the outcomes. You'll start by understanding how NLP and its various concepts work. Having got to grips with the basics, you'll explore important tools and libraries in Java for NLP, such as CoreNLP, OpenNLP, Neuroph, and Mallet. You'll then start performing NLP on different inputs and tasks, such as tokenization, model training, parts-of-speech and parsing trees. You'll learn about statistical machine translation, summarization, dialog systems, complex searches, supervised and unsupervised NLP, and more. By the end of this book, you'll have learned more about NLP, neural networks, and various other trained models in Java for enhancing the performance of NLP applications. What you will learn Understand basic NLP tasks and how they relate to one another Discover and use the available tokenization engines Apply search techniques to find people, as well as things, within a document Construct solutions to identify parts of speech within sentences Use parsers to extract relationships between elements of a document Identify topics in a set of documents Explore topic modeling from a document Who this book is for Natural Language Processing with Java is for you if you are a data analyst, data scientist, or machine learning engineer who wants to extract information from a language using Java. Knowledge of Java programming is needed, while a basic understanding of statistics will be useful but not mandatory.
    Note: Description based on online resource; title from title page (Safari, viewed August 27, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788993494/?ar
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  • 4
    Online Resource
    Online Resource
    Java : data science made easy : data collection, processing, analysis, and more : a course in two modules (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788479189 , 1788479181
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Java (Computer program language) ; Machine learning ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Data collection, processing, analysis, and more About This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples A highly practical course covering a broad set of topics - from the basics of Machine Learning to Deep Learning and Big Data frameworks. Who This Book Is For This course is meant for Java developers who are comfortable developing applications in Java, and now want to enter the world of data science or wish to build intelligent applications. Aspiring data scientists with some understanding of the Java programming language will also find this book to be very helpful. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing your existing Java stack, this book is for you! What You Will Learn Understand the key concepts of data science Explore the data science ecosystem available in Java Work with the Java APIs and techniques used to perform efficient data analysis Find out how to approach different machine learning problems with Java Process unstructured information such as natural language text or images, and create your own search Learn how to build deep neural networks with DeepLearning4j Build data science applications that scale and process large amounts of data Deploy data science models to production and evaluate their performance In Detail Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this course, we cover the basic as well as advanced data science concepts and how they are implemented using the popular Java tools and libraries.The course starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. You will examine the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation. Throughout this course, the chapters will illustrate a challenging data science problem, and then go on t...
    Note: Authors: Richard M. Reese, Jennifer L. Reese, Alexey Grigorev. Cf. Credits page. - "Learning path"--Cover. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed July 25, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781788475655/?ar
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  • 5
    Online Resource
    Online Resource
    Machine learning : end-to-end guide for Java developers : data analysis, machine learning and neural networks simplified (2017)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788629409 , 178862940X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Java (Computer program language) ; Machine learning ; Development ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Develop, Implement and Tuneup your Machine Learning applications using the power of Java programming About This Book Detailed coverage on key machine learning topics with an emphasis on both theoretical and practical aspects Address predictive modeling problems using the most popular machine learning Java libraries A comprehensive course covering a wide spectrum of topics such as machine learning and natural language through practical use-cases Who This Book Is For This course is the right resource for anyone with some knowledge of Java programming who wants to get started with Data Science and Machine learning as quickly as possible. If you want to gain meaningful insights from big data and develop intelligent applications using Java, this course is also a must-have. What You Will Learn Understand key data analysis techniques centered around machine learning Implement Java APIs and various techniques such as classification, clustering, anomaly detection, and more Master key Java machine learning libraries, their functionality, and various kinds of problems that can be addressed using each of them Apply machine learning to real-world data for fraud detection, recommendation engines, text classification, and human activity recognition Experiment with semi-supervised learning and stream-based data mining, building high-performing and real-time predictive models Develop intelligent systems centered around various domains such as security, Internet of Things, social networking, and more In Detail Machine Learning is one of the core area of Artificial Intelligence where computers are trained to self-learn, grow, change, and develop on their own without being explicitly programmed. In this course, we cover how Java is employed to build powerful machine learning models to address the problems being faced in the world of Data Science. The course demonstrates complex data extraction and statistical analysis techniques supported by Java, applying various machine learning methods, exploring machine learning sub-domains, and exploring real-world use cases such as recommendation systems, fraud detection, natural language processing, and more, using Java programming. The course begins with an introduction to data science and basic data science tasks such as data collection, data cleaning, data analysis, and data visualization. The next section has a detailed overview of statistical techniques, covering machine learning, neural networks, and deep learning. T...
    Note: "Learning path.". - Includes bibliographical references and index. - Description based on online resource; title from cover (Safari, viewed November 6, 2017)
    URL: https://learning.oreilly.com/library/view/-/9781788622219/?ar
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    MPI Ethno. Forsch.
  • 6
    Online Resource
    Online Resource
    Natural language processing with Java : explore various approaches to organize and extract useful text from unstructured data using Java (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781784398941 , 1784398942
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Community experience distilled
    Keywords: Natural language processing (Computer science) ; Java (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Explore various approaches to organize and extract useful text from unstructured data using Java In Detail Natural Language Processing (NLP) is an important area of application development and its relevance in addressing contemporary problems will only increase in the future. There has been a significant increase in the demand for natural language-accessible applications supported by NLP tasks. Natural Language Processing with Java will explore how to automatically organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. It covers concepts of NLP that even those of you without a background in statistics or natural language processing can understand. What You Will Learn Develop a deep understanding of the basic NLP tasks and how they relate to each other Discover and use the available tokenization engines Implement techniques for end of sentence detection Apply search techniques to find people and things within a document Construct solutions to identify parts of speech within sentences Use parsers to extract relationships between elements of a document Integrate basic tasks to tackle more complex NLP problems
    Note: Includes index. - Description based on online resource; title from cover page (Safari, viewed April 14, 2015)
    URL: https://learning.oreilly.com/library/view/-/9781784391799/?ar
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  • 7
    Online Resource
    Online Resource
    Understanding and using C pointers (2013)
    Sebastopol, CA : O'Reilly
    Details
    Language: English
    Pages: 1 online resource (1 v.) , ill.
    Keywords: C (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Improve your programming through a solid understanding of C pointers and memory management. With this practical book, you'll learn how pointers provide the mechanism to dynamically manipulate memory, enhance support for data structures, and enable access to hardware. Author Richard Reese shows you how to use pointers with arrays, strings, structures, and functions, using memory models throughout the book. Difficult to master, pointers provide C with much flexibility and power-yet few resources are dedicated to this data type. This comprehensive book has the information you need, whether you're a beginner or an experienced C or C++ programmer or developer. Get an introduction to pointers, including the declaration of different pointer types Learn about dynamic memory allocation, de-allocation, and alternative memory management techniques Use techniques for passing or returning data to and from functions Understand the fundamental aspects of arrays as they relate to pointers Explore the basics of strings and how pointers are used to support them Examine why pointers can be the source of security problems, such as buffer overflow Learn several pointer techniques, such as the use of opaque pointers, bounded pointers and, the restrict keyword
    Note: Includes index. - Description based on online resource; title from title page (Safari, viewed August 2, 2013)
    URL: https://learning.oreilly.com/library/view/-/9781449344535/?ar
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  • 8
    Online Resource
    Online Resource
    Learning network programming with Java : harness the hidden power of Java to build network-enabled applications with lower network traffic and faster processes (2015)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785882562 , 1785882562
    Language: English
    Pages: 1 online resource (1 volume) , illustrations.
    Series Statement: Community experience distilled
    Keywords: Java (Computer program language) ; Computer networks ; Programming ; Electronic books ; Electronic books ; local
    Abstract: Harness the hidden power of Java to build network-enabled applications with lower network traffic and faster processes About This Book Learn to deliver superior server-to-server communication through the networking channels Gain expertise of the networking features of your own applications to support various network architectures such as client/server and peer-to-peer Explore the issues that impact scalability, affect security, and allow applications to work in a heterogeneous environment Who This Book Is For Learning Network Programming with Java is oriented to developers who wish to use network technologies to enhance the utility of their applications. You should have a working knowledge of Java and an interest in learning the latest in network programming techniques using Java. No prior experience with network development or special software beyond the Java SDK is needed. Upon completion of the book, beginner and experienced developers will be able to use Java to access resources across a network and the Internet. What You Will Learn Connect to other applications using sockets Use channels and buffers to enhance communication between applications Access network services and develop client/server applications Explore the critical elements of peer-to-peer applications and current technologies available Use UDP to perform multicasting Address scalability through the use of core and advanced threading techniques Incorporate techniques into an application to make it more secure Configure and address interoperability issues to enable your applications to work in a heterogeneous environment In Detail Network-aware applications are becoming more prevalent and play an ever-increasing role in the world today. Connecting and using an Internet-based service is a frequent requirement for many applications. Java provides numerous classes that have evolved over the years to meet evolving network needs. These range from low-level socket and IP-based approaches to those encapsulated in software services. This book explores how Java supports networks, starting with the basics and then advancing to more complex topics. An overview of each relevant network technology is presented followed by detailed examples of how to use Java to support these technologies. We start with the basics of networking and then explore how Java supports the development of client/server and peer-to-peer applications. The NIO packages are examined as well as multitasking and how netwo...
    Note: Includes index. - Description based on online resource; title from cover page (Safari, viewed January 21, 2016)
    URL: https://learning.oreilly.com/library/view/-/9781785885471/?ar
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  • 9
    Online Resource
    Online Resource
    Natural Language Processing with Java Cookbook (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781789801156
    Language: English
    Pages: 1 online resource (386 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: A problem-solution guide to encountering various NLP tasks utilizing Java open source libraries and cloud-based solutions Key Features Perform simple-to-complex NLP text processing tasks using modern Java libraries Extract relationships between different text complexities using a problem-solution approach Utilize cloud-based APIs to perform machine translation operations Book Description Natural Language Processing (NLP) has become one of the prime technologies for processing very large amounts of unstructured data from disparate information sources. This book includes a wide set of recipes and quick methods that solve challenges in text syntax, semantics, and speech tasks. At the beginning of the book, you'll learn important NLP techniques, such as identifying parts of speech, tagging words, and analyzing word semantics. You will learn how to perform lexical analysis and use machine learning techniques to speed up NLP operations. With independent recipes, you will explore techniques for customizing your existing NLP engines/models using Java libraries such as OpenNLP and the Stanford NLP library. You will also learn how to use NLP processing features from cloud-based sources, including Google and Amazon Web Services (AWS). You will master core tasks, such as stemming, lemmatization, part-of-speech tagging, and named entity recognition. You will also learn about sentiment analysis, semantic text similarity, language identification, machine translation, and text summarization. By the end of this book, you will be ready to become a professional NLP expert using a problem-solution approach to analyze any sort of text, sentence, or semantic word. What you will learn Explore how to use tokenizers in NLP processing Implement NLP techniques in machine learning and deep learning applications Identify sentences within text and learn how to train specialized NER models Learn how to classify documents and perform sentiment analysis Find semantic similarities between text elements and extract text from a variety of sources Preprocess text from a variety of data sources Learn how to identify and translate languages Who this book is for This book is for data scientists, NLP engineers, and machine learning developers who want to perform their work on linguistic applications faster with the use of popular libraries on JVM machines. This book will help you build real-world NLP applications using a recipe-based approach. Prior knowledge of Natural Language Proc...
    Note: Online resource; Title from title page (viewed April 25, 2019)
    URL: lizenzpflichtig
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  • 10
    Online Resource
    Online Resource
    Wskaźniki w je̜zyku C : przewodnik (2014)
    Gliwice : Wydawnictwo HELION
    Details
    Language: Polish
    Pages: 1 online resource (1 v.) , ill.
    Keywords: C (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Jeśli chcesz błyskawicznie opanować programowanie w języku C, sięgnij po tę książkę! Gdy już poznasz podstawy, nauczysz się także korzystać ze wskaźników. To prawdziwa zmora wszystkich programistów, bowiem błędne wykorzystanie wskaźnika może w okamgnieniu zrujnować Twój program. Zobacz, jak tego uniknąć i zaprzyjaźnić się ze wskaźnikami. Inne książki opisują wskaźniki w jednym lub dwu rozdziałach, natomiast my poświęciliśmy im całą książkę. Dzięki temu dogłębnie poznasz ten mechanizm, zrozumiesz go i przekonasz się, że przy odrobinie uwagi nie jest on wcale taki straszny! W trakcie lektury wykorzystasz wskaźniki na funkcję, przygotujesz tablicę wskaźników oraz zobaczysz, jak współdziałają one z łańcuchami znaków. Twoją uwagę z pewnością zwrócą fragmenty omawiające zabezpieczenia oraz niewłaściwe wykorzystanie wskaźników. Książka ta jest jedyną pozycją na rynku w całości poświęconą wskaźnikom w języku C. To lektura obowiązkowa każdego programisty! Poznaj: koncepcję wskaźników zastosowanie tablic wskaźników funkcje dynamicznego alokowania pamięci zagrożenia wynikające ze stosowania wskaźników Odkryj tajniki wskaźników w języku C i wykorzystaj ich potencjał!
    Note: Authorized Polish translation of the English edition of Understanding and Using C Pointers. - Translator: Konrad Matuk. - Includes index. - Description based on online resource; title from title page (Safari, viewed Feb. 20, 2014)
    URL: lizenzpflichtig
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