Название: 99 Bottles of OOP 2nd Edition
Автор: Metz Sandi, Owen Katrina, Stankus, TJ
Издательство: Potato Canyon
Год: 2021
Формат: ePUB, MOBI
Размер: 14,7 Mb
Язык: English

99 Bottles of OOP is a practical guide to writing cost-effective, maintainable, and pleasing object-oriented code.
Now available in jаvascript, PHP, and Ruby!

Название: Bash Guide For Beginners: Everything You Need To Know About Bash Scripting
Автор: Gustavo Peevy
Издательство: Amazon.com Services LLC
Год: 2021
Страниц: 204
Язык: английский
Формат: pdf, epub
Размер: 10.2 MB

This Bash Scripting Guide is an introduction to basic and advanced concepts of the bash shell. It teaches both newcomers and long-time users the best, safest, and most robust ways of writing powerful bash scripts as well as making efficient and speedy interactive use of the shell. Bash Scripting Guide is focused on the Bourne-again shell (BASH), the concepts presented can be applied to virtually any shell, including Bourne (sh), Korn (kc), C (csh), Z (zsh), and the tee-shell (tsch). For those just beginning, by the end of this book, you will be able to write shell scripts and automate tasks with ease. If you are transitioning from another programming language, this guide will build on your existing knowledge and turn you into an expert in no time. For those with experience in Bash scripting, the later chapters will hone your expertise while presenting advanced concepts such as file descriptor duplication, process substitution, traps, and more.

Название: Knowledge Graphs for EXplainable Artificial Intelligence: Foundations, Applications and Challenges
Автор: Ilaria Tiddi, Freddy Lecue
Издательство: IOS Press, Akademische Verlagsgesellschaft AKA GmbH
Год: 2020
Страниц: 314
Язык: английский
Формат: pdf (true)
Размер: 11.3 MB

The latest advances in Artificial Intelligence and (deep) Machine Learning in particular revealed a major drawback of modern intelligent systems, namely the inability to explain their decisions in a way that humans can easily understand. While eXplainable AI rapidly became an active area of research in response to this need for improved understandability and trustworthiness, the field of Knowledge Representation and Reasoning (KRR) has on the other hand a long-standing tradition in managing information in a symbolic, human-understandable form. This book provides the first comprehensive collection of research contributions on the role of knowledge graphs for eXplainable AI (KG4XAI), and the papers included here present academic and industrial research focused on the theory, methods and implementations of AI systems that use structured knowledge to generate reliable explanations. Introductory material on knowledge graphs is included for those readers with only a minimal background in the field, as well as specific chapters devoted to advanced methods, applications and case-studies that use knowledge graphs as a part of knowledge-based, explainable systems (KBX-systems).

Название: XQuery for Humanists (Coding for Humanists)
Автор: Clifford B. Anderson, Joseph C. Wicentowski
Издательство: Texas A&M University Press
Год: 2020
Страниц: 351
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

XQuery is the best language for querying, manipulating, and transforming XML and JSON documents. Because XML is in many ways the lingua franca of the digital humanities, learning XQuery empowers humanists to discover and analyze their data in new ways. Until now, though, XQuery has been difficult to learn because there was no textbook designed for non- or beginner programmers. XQuery for Humanists fills this void with an approachable guidebook aimed directly at digital humanists. Clifford B. Anderson and Joseph C. Wicentowski introduce XQuery in terms accessible to humanities scholars and do not presuppose any prior background in programming. It provides an informed, opinionated overview and recommends the best implementations, libraries, and paradigms to empower those who need it most. Emphasizing practical applicability, the authors go beyond the XQuery language to include the basics of underlying standards like XPath, related standards like XQuery Full Text and XQuery Update, and explain the difference between XQuery and languages like Python and R.

Название: Bayesian Modeling of Spatio-Temporal Data with R
Автор: Sujit K. Sahu
Издательство: CRC Press
Год: 2022
Формат: PDF
Страниц: 434
Размер: 61 Mb
Язык: English

Applied sciences, both physical and social, such as atmospheric, biological, climate, demographic, economic, ecological, environmental, oceanic and political, routinely gather large volumes of spatial and spatio-temporal data in order to make wide ranging inference and prediction. Ideally such inferential tasks should be approached through modelling, which aids in estimation of uncertainties in all conclusions drawn from such data. Unified Bayesian modelling, implemented through user friendly software packages, provides a crucial key to unlocking the full power of these methods for solving challenging practical problems.

Название: Python for Beginners: Data Analysis, Machine Learning, and Data Science Projects. A Crash Course in Python for Absolute Beginners (2022 Guide)
Автор: Ike Beck
Издательство: Amazon.com Services LLC
Год: 2021
Страниц: 100
Язык: английский
Формат: pdf, epub
Размер: 15.5 MB

Python is a popular language of programming that is taught and used in both academic institutions and businesses. Python's allure is hidden behind the fact that it has a plethora of applications in a variety of industries. Python is disliked by the majority of people because it is used to create artificial intelligence models. They are concerned that these Python-powered AI models will drive people out of multiple industries and take their jobs. They give the example of Tesla's driverless taxi project, in which Tesla pretends to replace Uber's taxis in the US market. The truth, on the other hand, is quite different. Indeed, Python-based AI models will create far more jobs than they will eliminate. Creating these models, for example, will become its own industry.

Название: Artificial Intelligence in Precision Health: From Concept to Applications
Автор: Debmalya Barh, PhD
Издательство: Academic Press, Elsevier
Год: 2020
Страниц: 530
Язык: английский
Формат: pdf (true)
Размер: 17.6 MB

Artificial Intelligence in Precision Health: From Concept to Applications provides a readily available resource to understand Artificial Intelligence (AI) and its real time applications in precision medicine in practice. Written by experts from different countries and with diverse background, the content encompasses accessible knowledge easily understandable for non-specialists in computer sciences. The book discusses topics such as cognitive computing and emotional intelligence, Big Data analysis, clinical decision support systems, Deep Learning, personal omics, digital health, predictive models, prediction of epidemics, drug discovery, precision nutrition and fitness. Computational approaches such as genetic algorithm, support vector machines, artificial neural network, decision trees, natural language processing, hybrid methods, cognitive computing, etc., introduced Artificial Intelligence (AI) into health care, which became a game changer in personalized medicine or precision health care in terms of time, cost, and personalization.

Название: Handbuch Infrastructure as Code: Prinzipien, Praktiken und Patterns für eine cloudbasierte IT-Infrastruktur
Автор: Kief Morris
Издательство: O’Reilly Media, Inc.
Год: 2022
Страниц: 450
Язык: немецкий
Формат: pdf, epub
Размер: 12,7 MB

Cloud-Infrastrukturen erfolgreich automatisieren: Strategien für die Praxis. In diesem praktischen Handbuch beschreibt Kief Morris von ThoughtWorks, wie Sie Ihre IT-Infrastruktur im Cloud-Zeitalter erfolgreich aufsetzen und betreiben. Sie erfahren, wie Sie hierfür die von zahlreichen DevOps-Teams entwickelten und erprobten Prinzipien, Praktiken und Patterns nutzen können.

Название: Data Structure and Algorithmic Thinking: Self-Driving Car
Автор: Khoo Kay Yong
Издательство: E-Learn Dot Com Limited
Серия: Coding with Micro:bits
Год: 2021
Страниц: 133
Язык: английский
Формат: pdf, epub
Размер: 16.4 MB

Data Structure is a way of collecting and organising data in such a way that we can perform operations on these data in an effective way. Data structure is about rendering data elements in terms of some relationship, for better organisation and storage. For example, we have some data which has, distance and location in the example. The "location" is of String data type and distance is of integer data type. An algorithm is a method to solve problem that consists of exactly a list of rules with a well-defined sequence to follow in order to solve the problem. Algorithmic thinking consists a pool of abilities: to analyse a given problem, to specify the problem precisely, to find the basic actions that are adequate to the given problem, to construct a correct algorithm to a given problem using the workable actions, to think about all possible cases of a problem and to improve the efficiency of an algorithm. In this module, Algorithm Skills and Data Structure are added into a story. The learners will apply their algorithmic thinking skills to analyse the movement of a robot, i.e., the beginning and the ending, to specify the steps and the directions of the movements, then he/she will code the robot and to execute and find out the answers.

Название: Data Structure and Algorithmic Thinking with Python: Data Structure and Algorithmic Puzzles 2020
Автор: Narasimha Karumanchi
Издательство: CareerMonk Publications
Год: 2020
Страниц: 436
Язык: английский
Формат: pdf
Размер: 10.2 MB

The study of algorithms and data structures is central to understanding what computer science is all about. Learning computer science is not unlike learning any other type of difficult subject matter. The only way to be successful is through deliberate and incremental exposure to the fundamental ideas. A beginning computer scientist needs practice so that there is a thorough understanding before continuing on to the more complex parts of the curriculum. In addition, a beginner needs to be given the opportunity to be successful and gain confidence. This textbook is designed to serve as a text for a first course on data structures and algorithms. In this book, we cover abstract data types and data structures, writing algorithms, and solving problems. We look at a number of data structures and solve classic problems that arise. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science. All the code in this book are written in Python. It contains many programming puzzles that not only encourage analytical thinking, but also prepares readers for interviews.