Название: Pragmatic Deep Learning for Dummies
Автор: Benjamin Young
Издательство: Amazon Digital Services LLC
Год: 2019
Язык: английский
Формат: epub, azw3
Размер: 10.1 MB

AI especially Deep Learning has made tremendous progress in recent years. It start to spread to all industries. Quote from Andrew Ng, a famous AI researcher:“AI is the new electricity. About 100 years ago, electricity transformed every major industry. AI has advanced tothe point where it has the power to transform every major sector in coming years. "Unless you are a refresh graduated student with AI/deep learning major, many of us do not have a formal machine learning/deep learning training before, so it is time to keep updated with latest technology.

Название: The Intuitive Guide to Data Structures and Algorithms
Автор: Parker Phinney
Издательство: Amazon Digital Services LLC
ASIN: B07FDLH599
Год: 2018
Страниц: 131
Язык: английский
Формат: epub, azw3, pdf (conv)
Размер: 10.1 MB

This is not a freaking textbook. No confusing academic jargon. No long lists of properties to memorize. No proofs. Because that stuff doesn’t help you actually get it. Here’s what does: Learning what to picture in your head when you think of a dynamic array or a hash map. Learning how to think in algorithms. That’s what this guide is focused on - giving you a visual, intuitive sense for how data structures and algorithms actually work. So if you’ve got a big coding interview coming up, or you never learned data structures and algorithms in school, or you did but you’re kinda hazy on how some of this stuff fits together... This guide will fill in the gaps in your knowledge and make you say, "Oooh, that’s how that works." We’ll walk you through it all, step by step. Starting from the beginning.

Название: Deep Learning: Convergence to Big Data Analytics
Автор: Murad Khan, Bilal Jan, Haleem Farman
Издательство: Springer
Серия: SpringerBriefs in Computer Science
ISBN: 9811334587
Год: 2019
Страниц: 93
Язык: английский
Формат: pdf (true), epub
Размер: 14.6 MB

This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various challenges, such as fast, accurate and efficient processing of big data in real-time. In addition, the Internet of Things is progressively increasing in various fields, like smart cities, smart homes, and e-health. As the enormous number of connected devices generate huge amounts of data every day, we need sophisticated algorithms to deal, organize, and classify this data in less processing time and space. Similarly, existing techniques and algorithms for deep learning in big data field have several advantages thanks to the two main branches of the deep learning, i.e. convolution and deep belief networks. This book offers insights into these techniques and applications based on these two types of deep learning.

Название: Introduction to Cryptography: Principles and Applications, 3rd edition
Автор: Hans Delfs and Helmut Knebl
Издательство: Springer
Год: 2015
Формат: PDF
Размер: 5 Мб
Язык: английский / English

The first part of this book covers the key concepts of cryptography on an undergraduate level, from encryption and digital signatures to cryptographic protocols. Essential techniques are demonstrated in protocols for key exchange, user identification, electronic elections and digital cash. In the second part, more advanced topics are addressed, such as the bit security of one-way functions and computationally perfect pseudorandom bit generators. The security of cryptographic schemes is a central topic. Typical examples of provably secure encryption and signature schemes and their security proofs are given. Though particular attention is given to the mathematical foundations, no special background in mathematics is presumed. The necessary algebra, number theory and probability theory are included in the appendix. Each chapter closes with a collection of exercises.

Название: Turbo Pascal. Практикум
Автор: Немнюгин С.А.
Издательство: Питер
Год: 2001
Страниц: 254
ISBN: 5-272-00068-4
Формат: PDF
Размер: 15 Mб
Язык: русский

Практикум является пособием для практических занятий по программированию на языке Turbo Pascal и дополняет собой пользующийся заслуженным успехом у читателей учебник того же автора. Десять занятий Практикума содержат необходимый минимум теоретических сведений, примеры программ с подробными комментариями к ним, упражнения и задания для самостоятельной работы.

Название: Improving Information Security Practices Through Computational Intelligence
Автор: Wasan Shaker Awad and El Sayed M. El-Alfy
Издательство: IGI Global
Год: 2015
Формат: PDF
Размер: 25 Мб
Язык: английский / English

The recent explosion in complex global networking architectures has spurred a concomitant rise in the need for robust information security. Further, as computing power increases exponentially with every passing year, so do the number of proposed cryptographic schemata for improving and ensuring the encryption integrity of cutting-edge infosec protocols.

Название: Virtualizing SQL Server with VMware: Doing IT Right
Автор: Michael Corey and Jeff Szastak
Издательство: VMware Press
Год: 2014
Формат: EPUB
Размер: 27 Мб
Язык: английский / English

The start-to-finish guide to virtualizing business-critical SQL Server databases on VMware vSphere 5. By virtualizing business-critical databases, enterprises can drive far more value from existing IT infrastructure. But squeezing maximum performance out of a virtualized database instance is an art as much as a science. This indispensable start-to-finish guide brings together all the techniques, tips, and insights you need to succeed.

Название: Evolutionary Learning: Advances in Theories and Algorithms
Автор: Zhi-Hua Zhou, Yang Yu, Chao Qian
Издательство: Springer
Год: 2019
Страниц: 361
Язык: английский
Формат: pdf (true), djvu
Размер: 10.1 MB

Many Machine Learning (ML) tasks involve solving complex optimization problems, such as working on non-differentiable, non-continuous, and non-unique objective functions; in some cases it can prove difficult to even define an explicit objective function. Evolutionary learning applies evolutionary algorithms to address optimization problems in machine learning, and has yielded encouraging outcomes in many applications. However, due to the heuristic nature of evolutionary optimization, most outcomes to date have been empirical and lack theoretical support. This shortcoming has kept evolutionary learning from being well received in the machine learning community, which favors solid theoretical approaches. Machine Learning is a central topic of Artificial Intelligence (AI). It aims at learning generalizable models from data, with which the system performance can be improved. As nowadays data can be continually acquired and accumulated in numerous applications such as image recognition and commodity recommendation, machine learning has been playing an increasingly important role in the successes of these applications.

Название: Achieving DevOps: A Novel About Delivering the Best of Agile, DevOps, and Microservices
Автор: Dave Harrison, Knox Lively
Издательство: Apress
Год: 2019
Страниц: 515
Язык: английский
Формат: pdf (true), epub
Размер: 12.05 MB

Ben is stuck. A development lead with a strong vision for how the intersection of development and operations at his office can be improved, he can’t help but feel overwhelmed and discouraged by common problems such as slow turnaround time, rushed and ineffective handover documentation, mounting technical debt, and a lagging QA process. What steps should Ben take to build the momentum needed to create positive changes within his company?

Название: Numerical Methods of Mathematics Implemented in Fortran
Автор: Sujit Kumar Bose
Издательство: Springer
Год: 2019
Страниц: 479
Язык: английский
Формат: pdf (true), djvu
Размер: 10.1 MB

The computer codes have been written in the Fortran programming language, which is the traditional language for scientific computation. Fortran has a vast repository of source codes used in real-world applications and has continuously been upgraded in line with the computing capacity of the hardware. The language is fully backwards compatible with its earlier versions, facilitating integration with older source codes. For writing the computer codes, I have chosen to use the Fortran programming language. Fortran is a powerful, easy-to-learn and traditional language for scientific computation in which there are a number of inbuilt intrinsic functions.