Название: Core Java, Vol. II-Advanced Features, 12th Edition
Автор: Cay S. Horstmann
Издательство: Addison-Wesley Professional
Год: 2022
Формат: ePUB
Страниц: 944
Размер: 14,8 Mb
Язык: English

The #1 Java Guide for Serious Programmers: Fully Updated through Java 17
Core Java, Volume II: Fundamentals, Twelfth Edition, is the definitive guide to writing robust, maintainable code. Whatever version of Java you are usingup to and including Java 17this book will help you achieve a deep and practical understanding of the language and APIs. With with authoritative coverage of enterprise programming, networking, databases, security, modularization, internationalization, code processing, native methods, and more. Cay S. Horstmann explores sophisticated new features with depth and completeness, demonstrating how to use them to build professional-quality applications

Название: Computational Analysis of Storylines: Making Sense of Events (Studies in Natural Language Processing)
Автор: Tommaso Caselli, Eduard Hovy
Издательство: Cambridge University Press
Год: 2021
Страниц: 275
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Event structures are central in Linguistics and Artificial Intelligence research: people can easily refer to changes in the world, identify their participants, distinguish relevant information, and have expectations of what can happen next. Part of this process is based on mechanisms similar to narratives, which are at the heart of information sharing. But it remains difficult to automatically detect events or automatically construct stories from such event representations. This book explores how to handle today's massive news streams and provides multidimensional, multimodal, and distributed approaches, like automated deep learning, to capture events and narrative structures involved in a 'story'. This overview of the current state-of-the-art on event extraction, temporal and casual relations, and storyline extraction aims to establish a new multidisciplinary research community with a common terminology and research agenda. Graduate students and researchers in natural language processing, computational linguistics, and media studies will benefit from this book.

Название: Black Hat Python: программирование для хакеров и пентестеров, 2-е изд
Автор: Зейтц Д., Арнольд Т.
Издательство: Питep
Год: 2022
Формат: True PDF
Страниц: 224
Размер: 10 Mb
Язык: Русский

Когда речь идет о создании мощных и эффективных хакерских инструментов, большинство аналитиков по безопасности выбирают Python. Во втором издании бестселлера Black Hat Python вы исследуете темную сторону возможностей Python — все от написания сетевых снифферов, похищения учетных данных электронной почты и брутфорса каталогов до разработки мутационных фаззеров, анализа виртуальных машин и создания скрытых троянов.

Название: Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications
Автор: Om Prakash Jena, Bharat Bhushan, Utku Kose
Издательство: CRC Press
Год: 2022
Страниц: 292
Язык: английский
Формат: pdf (true)
Размер: 14.3 MB

Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary Machine Learning (ML) and Deep Learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging, automation, robotic surgery, electronic smart records creation, outbreak prediction, medical image analysis, and radiation treatments.

Название: Prediction and Analysis for Knowledge Representation and Machine Learning
Автор: Avadhesh Kumar, Shrddha Sagar, T. Ganesh Kumar
Издательство: CRC Press
Год: 2022
Страниц: 232
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

Number of approaches are being defined for statistics and Machine Learning. These approaches are used for the identification of the process of the system and the models created from the system's perceived data, assisting scientists in the generation or refinement of current models. Machine Learning (ML) is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to Machine Learning algorithms. It has a significant impact on comprehending difficult scientific problems.

Название: Quantum Computing in Action
Автор: Johan Vos
Издательство: Manning Publications
Год: 2022
Формат: ePUB
Страниц: 410
Размер: 10 Mb
Язык: English

Quantum computing is on the horizon and you can get started today! This practical, clear-spoken guide shows you don’t need a physics degree to write your first quantum software.

Название: Data Privacy
Автор: Nishant Bhajaria
Издательство: Manning Publications
Год: 2022
Формат: ePUB
Страниц: 365
Размер: 10 Mb
Язык: English

Data Privacy teaches you to design, develop, and measure the effectiveness of privacy programs. You’ll learn from author Nishant Bhajaria, an industry-renowned expert who has overseen privacy at Google, Netflix, and Uber. The terminology and legal requirements of privacy are all explained in clear, jargon-free language. The book’s constant awareness of business requirements will help you balance trade-offs, and ensure your user’s privacy can be improved without spiraling time and resource costs.

Название: Regression Models for Data Science in R: Statistical inference for Data Science
Автор: Yassine Mousaif
Издательство: Independently published
Год: 2022
Страниц: 132
Язык: английский
Формат: pdf, epub
Размер: 10.2 MB

What's Special about this Book: The ideal reader for this book will be quantitatively literate and has a basic understanding of statistical concepts and R programming. The student should have a basic understanding of statistical inference such as contained in "Statistical inference for Data Science". The book gives a rigorous treatment of the elementary concepts of regression models from a practical perspective. After reading the book and watching the associated videos, students will be able to perform multivariable regression models and understand their interpretations. Regression models are the workhorse of Data Science. They are the most well described, practical and theoretically understood models in statistics. A data scientist well versed in regression models will be able to solve and incredible array of problems. Perhaps the key insight for regression models is that they produce highly interpretable model fits. This is unlike Machine Learning algorithms, which often sacrifice interpretability for improved prediction performance or automation.

Название: Handbook on Computational Intelligence (In 2 Volumes)
Автор: Plamen Parvanov Angelov
Издательство: World Scientific Publishing
Серия: Series on Computational Intelligence
Год: 2016
Страниц: 957
Язык: английский
Формат: pdf, epub
Размер: 30.5 MB

With the Internet, the proliferation of Big Data, and autonomous systems, mankind has entered into an era of 'digital obesity'. In this century, Computational Intelligence (CI), such as thinking machines, have been brought forth to process complex human problems in a wide scope of areas - from social sciences, economics and biology, medicine and social networks, to cyber security. The Handbook of Computational Intelligence (in two volumes) prompts readers to look at these problems from a non-traditional angle. It takes a step by step approach, supported by case studies, to explore the issues that have arisen in the process. The Handbook covers many classic paradigms, as well as recent achievements and future promising developments to solve some of these very complex problems. Volume one explores the subjects of fuzzy logic and systems, artificial neural networks (ANNs), and learning systems. Volume two delves into evolutionary computation, hybrid systems, as well as the applications of Computational Intelligence in decision making, the process industry, robotics, and autonomous systems. This work is a ""one-stop-shop"" for beginners, as well as an inspirational source for more advanced researchers. It is a useful resource for lecturers and learners alike.

Название: Deep Learning, Machine Learning and IoT in Biomedical and Health Informatics: Techniques and Applications
Автор: Sujata Dash, Subhendu Kumar Pani, Joel Rodrigues
Издательство: CRC Press
Год: 2022
Страниц: 382
Язык: английский
Формат: pdf (true)
Размер: 72.2 MB

The novel applications of Internet of Things (IoT) in health care data analytics can be regarded as an emerging field in Computer Science, medicine, biology application, natural environmental engineering, and pattern recognition. Deep Learning (DL) has been showing tremendous improvement in accuracy, robustness, and cross- language generalizability over conventional approaches. Machine Learning (ML) can provide computational methods for accumulating, updating, and changing knowledge in the intelligent systems, especially learning mechanisms that help us induce knowledge from the data. ML is helpful in the cases where direct algorithmic solutions are unavailable, lack formal models, or require knowledge about the application domain that is skimpy. IoT is anticipated to have the capability to change the way we work and live. These computing methods also play a significant role in the design and optimization of diverse engineering disciplines.