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Simpson A: Python Automation For Dummies

Python Automation For Dummies

Elevate your software testing approach with a methodology from industry leaders who dedicated their careers to studying, practicing, and teaching the craft of testing. Dive into the world of expert software testing with Taking Testing Seriously: The Rapid Software Testing Approach. This book arms software professionals with the knowledge required to master the Rapid Software Testing (RST) methodology. Written by two co-creators of the RST approach and supplemented by material from respected testers who offer valuable insights, it is an essential read for anyone seeking excellence in the craft of testing. Taking Testing Seriously offers a rich exploration of the RST methodology through insightful interviews, expert discussions, practical case studies, and real-world examples. It thoroughly covers key topics such as the psychology of testing, the science behind it, the fundamental processes and heuristics of test design, and much more. This book provides concrete strategies for addressing common software testing challenges and integrating new solutions with existing systems. You will: <ul> <li>Gain insights from experienced software testers through in-depth interviews and expert advice</li> <li>Learn how to the skills of testing are needed more than ever in an AI-powered IT industry</li> <li>Discover strategies to leverage the latest automation technologies to refine and expedite your testing processes</li> <li>Escape from the echo chamber of "best practices" and learn to think critically about testing</li> </ul> Focusing on the mindset and skillset of excellent testing, Taking Testing Seriously is a must-have resource for software engineers and technical leaders eager to improve their testing proficiency. Whether you are looking to advance your career or simply want to ensure your next project meets the highest standards of quality, this book provides the tools you need. Order your copy today and start transforming the way you and your team approach software testing.

The Rapid Software Testing Approach

Taking Testing Seriously

Synthetic Media, Deepfakes, and Cyber Deception: Attacks, Analysis, and Defenses introduces the only analytical Synthetic Media Analysis Framework (SMAF) to help describe cyber threats and help security professionals anticipate and analyze attacks. This framework encompasses seven dimensions: Credibility, Control, Medium, Interactivity, Familiarity, Intended Target, and Evocation. Synthetic media is a broad term that encompasses the artificial manipulation, modification, and production of information, covering a spectrum from audio-video deepfakes to text-based chatbots. Synthetic media provides cyber attackers and scammers with a game-changing advantage over traditional ROSE attacks because they have the potential to convincingly impersonate close associates through text, imagery, voice, and video. This burgeoning threat has yet to be meaningfully addressed through any written treatment on the topic. The book is co-authored by three cyber influence and deception experts who have gained deep knowledge and experience on the topic through diverse, true operational pathways and backgrounds. The diversity and perspectives of the author team makes the content in the book the broadest and deepest treatment of synthetic media attacks available to readers.

Attacks, Analysis, and Defenses

Synthetic Media, Deepfakes, and Cyber Deception

An engaging, illustrated collection of insights revealing the practices and principles that expert software designers use to create great software.

66 Ways Experts Think

Software Design Decoded

Learn dozens of tried-and-true strategies to find and fix coding mistakes with this efficient debugging guide that slashes the time required for this tedious task. Most programmers dread debugging, but it remains a critical skill and one often learned through trial and error. This book offers a shortcut, distilling the experience of top-tier game designer Johannes Kuhlmann – who has worked on popular games like Valheim and Saints Row – into clear, practical strategies for debugging complex software in record time. This book offers more than 25 reliable strategies to tackle bugs at every level of development, helping to ensure that quality products go to market on schedule. Each chapter blends technical advice with instructive examples from the author’s own career, offering widely applicable, language-agnostic techniques from which both novice programmers and seasoned developers will benefit. The Debugging Handbook is not just a manual to reach for time and again but a mentor, helping programmers develop the mindset to quickly squash any bug.

The Debugging Handbook

Quantum Process Algebra introduces readers to the algebraic properties and laws for quantum computing. The book provides readers with all aspects of algebraic theory for quantum computing, including the basis of semantics and axiomatization for quantum computing. With the assumption of a quantum system, readers will learn to solve the modelling of the three main components in a quantum system: unitary operator, quantum measurement, and quantum entanglement, with full support of quantum and classical computing in closed systems. Next, the book establishes the relationship between probabilistic quantum bisimilarity and classical probabilistic bisimilarity, including strong probabilistic bisimilarity and weak probabilistic bisimilarity, which makes an axiomatization of quantum processes possible. With this framework, quantum and classical computing mixed processes are unified with the same structured operational semantics. Finally, the book establishes a series of axiomatizations of quantum process algebras. These process algebras support nearly all main computation properties. Quantum and classical computing in closed quantum systems are unified with the same equational logic and the same structured operational semantics under the framework of ACP-like probabilistic process algebra. This unification means that the mathematics in the book can be used widely for verification of quantum and classical computing mixed systems, for example, most quantum communication protocols. ACP-like axiomatization also inherits the advantages of ACP, for example, and modularity means that it can be extended in an elegant way.

Quantum Process Algebra

Embedded Systems in Automotive Applications

Written by a data scientist with decades of practical experience on some of the most challenging datasets, this book caters to both novices and professionals working in the fields of data science and machine learning. It enables novices to enter these fields with confidence and ease. There are no formal prerequisites. An introduction to Python is included. The book then proceeds to cover some of the language's most advanced features. The mathematical foundations that follow are meticulously explained. The discussion then proceeds to a practical consideration of data science and machine learning. The material is delivered through case studies developed on real datasets. The reader is invited to follow these case studies, and so develop experience in working with real data. Numerous solved exercises make this work suitable for self-study. The contents of this book have been taught by the author to students of different age groups and levels of experience at Imperial College London and at the Thalesians Intensive Summer School in Artificial Intelligence over the years.

Introduction To Python For Quantitative Finance, An: From Scratch To Productivity

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Advances in Computers

Quantum Machine Learning (QML): Platform, Tools and Applications: Volume 140

Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence empowers qualitative and mixed methods researchers in the data science movement by offering no-code, cost-free software access so that they can apply cutting-edge and innovative methods to synthetize qualitative data. The book builds on the idea that qualitative and mixed methods researchers should not have to learn to code to benefit from rigorous open-source, cost-free software that uses artificial intelligence, machine learning, and data visualization tools-just as people do not need to know C++ or TypeScript to benefit from Microsoft Word. The real barrier is the hundreds of R code lines required to apply these concepts to their databases. By removing the coding proficiency hurdle, this book will empower their research endeavors and help them become active members of and contributors to the applied data science community. The book offers a comprehensive explanation of data science and machine learning methodologies, along with access to software application tools to implement these techniques without any coding proficiency. The book addresses the need for innovative tools that enable researchers to tap into the insights that come out of cutting-edge data science tools with absolutely no computer language literacy requirements.

Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence

This unique compendium presents the basics of the theory of computing at a level and in a manner that can be easily understood by computer science students in a large university. It offers the student a firm foundation in logical reasoning and covers many traditional topics in unconventional ways.The useful reference text benefits professionals, academics, researchers and undergraduate students in the area of theoretical computer science.

Foundation Of Computation: Languages And Machines

Python Automation For Dummies

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