*A practical guide to Machine Learning and its applications in translation, in the specific context of translator/localizer training and education * written to be equally useful for both students on translation studies courses and professionals in the area of localization *Unlike existing titles, it focuses on bridging the gap between machine learning technology in the humanities and translation practice and takes a bottom-up, relevancy approach to Machine Learning in Translation

The go-to guide in machine learning projects from design to production. No ML skills required! In Managing Machine Learning Projects, you will learn essential machine learning project management techniques, including: Understanding an ML project's requirements Setting up the infrastructure for the project and resourcing a team Working with clients and other stakeholders Dealing with data resources and bringing them into the project for use Handling the lifecycle of models in the project Managing the application of ML algorithms Evaluating the performance of algorithms and models Making decisions about which models to adopt for delivery Taking models through development and testing Integrating models with production systems to create effective applications Steps and behaviours for managing the ethical implications of ML technology About the technology Companies of all shapes, sizes, and industries are investing in machine learning (ML). Unfortunately, around 85% of all ML projects fail. Managing machine learning projects requires adopting a different approach than you would take with standard software projects. You need to account for large and diverse data resources, evaluate and track multiple separate models, and handle the unforeseeable risk of poor performance. Never fear — this book lays out the unique practices you will need to ensure your projects succeed!

A Brief History of Brains bridges the gap between AI and neuroscience by telling the evolutionary story of how the brain came to be. The entirety of the human brain’s 4-billion-year story can be summarised as the culmination of five evolutionary breakthroughs, starting from the very first brains, all the way to the modern human brains. Each breakthrough emerged from new sets of brain modifications, and equipped animals with a new suite of intellectual faculties. These five breakthroughs are the organising map to this book, and they make up our itinerary for our adventure back in time. Each breakthrough also has fascinating corollaries to breakthroughs in AI. Indeed, there will be plenty of such surprises along the way. For instance: the innovation that enabled AI to beat humans in the game of Go – temporal difference reinforcement learning – was an innovation discovered by our fish ancestors over 500 million years ago. The solutions to many of the current mysteries in AI – such as ‘common sense’ – can be found in the tiny brain of a mouse. Where do emotions come from? Research suggests that they may have arisen simply as a solution to navigation in ancient worm brains. Unravelling this evolutionary story will reveal the hidden features of human intelligence and with them, just how your mind came to be.

Focuses on several core aspects of Industry 4.0 on computer vision & imaging. Highlights several exciting techniques for disease prediction, NLP, image captioning, flood level assessment, crop classifications, and fabrication of smart wheelchairs. Covers several chapters on Natural Language Processing (NLP), focusing on Bangla language. Chapters presented in a step-by-step manner so that young minds can understand and implement easily.

Discover how visualization turns data into action Tableau gives you the power to understand your data and put it in a format that is appealing and meaningful for everyone who needs to see it. Tableau For Dummies walks you through the steps to turn your data into a story that inspires action. This easy-to-understand guide offers insights from an enterprise data pro on how to transform data into a clear and memorable visual presentation. Navigate the Tableau user interface and connect to data sources Use drag-and-drop features to create stunning visualizations Work with templates, add graphs, and create clear charts Export your visualizations to multiple formats for easy sharing This is the perfect Dummies software guide for business professionals who need to better derive value from that all-important data.

Explores text mining and IoT applications for monitoring and controlling smart industrial systems Describes the key principles and techniques for Big-data analytics, security, and optimization for industrial applications. Provides context-aware insights, human-centric industry, smart computing for next-generation industry

Cybersecurity attacks grow more complex every day. The first edition of Wilson's COMPTIA PENTEST+ GUIDE TO PENETRATION TESTING helps you gain the knowledge and skills necessary to analyze systems in the same way hackers do. It provides the information you need to successfully pass the CompTIA PenTest+ PTO-002 certification exam and contains detailed examples, projects, and hands-on activities (including virtual machine labs and interactive online features) where you can practice using the actual tools and methodologies needed to be a successful penetration tester. The author begins by exploring the concept of penetration testing, and then walks you through the process of building your own penetration testing lab of virtual machines (hosted on your own computer, which is used to practice the use of pen testing tools and methods). A final project guides you in the creation of a penetration testing report that includes all the areas covered in earlier modules.

- The book discusses the recent techniques in NGS data analysis which is the most needed material by biologists (students and researchers) in the wake of numerous genomic projects and the trend toward genomic research. - The book includes both theory and practice for the NGS data analysis. So, readers will understand the concept and learn how to do the analysis using the most recent programs. - The steps of application workflows are written in a manner that can be followed for related projects. - Each chapter includes worked examples with real data available on the NCBI databases. Programming codes and outputs are accompanied with explanation. - The book content is suitable as teaching material for biology and bioinformatics students. Meets the requirements of a complete semester course on Sequencing Data Analysis Covers the latest applications for Next Generation Sequencing Covers data reprocessing, genome assembly, variant discovery, gene profiling, epigenetics, and metagenomics

Unique selling point: Comprehensive tome on developing and implementing parallel and distributed systems Core audience: Computer science title for systems developers and designers Place in the market: Professional title for a niche segment of developers and programmers

An Introduction to Numerical Methods: A MATLAB® Approach, Fifth Edition continues to offer readers an accessible and practical introduction to numerical analysis. It presents a wide range of useful and important algorithms for scientific and engineering applications, using MATLAB to illustrate each numerical method with full details of the computed results so that the main steps are easily visualized and interpreted. This edition also includes new chapters on Approximation of Continuous Functions and Dealing with Large Sets of Data. Features: Covers the most common numerical methods encountered in science and engineering Illustrates the methods using MATLAB Ideal as an undergraduate textbook for numerical analysis Presents numerous examples and exercises, with selected answers provided at the back of the book Accompanied by downloadable MATLAB code hosted at https/www.routledge.com/ 9781032406824

Cloud computing, the Internet of Things (IoT), and big data are three significant technological trends affecting the world's largest corporations. This book discusses big data, cloud computing, and the IoT, with a focus on the benefits and implementation problems. In addition, it examines the many structures and applications pertinent to these disciplines. Also, big data, cloud computing, and the IoT are proposed as possible study avenues. Features: Informs about cloud computing, IoT and big data, including theoretical foundations and the most recent empirical findings Provides essential research on the relationship between various technologies and the aggregate influence they have on solving real-world problems Ideal for academicians, developers, researchers, computer scientists, practitioners, information technology professionals, students, scholars, and engineers exploring research on the incorporation of technological innovations to address contemporary societal challenges

A very concise guide to a popular programming language, so there is a healthy demand for content which teaches who to utilize JavaScript. The book's broad coverage (paired with being compact) makes it more appealing than competitor's books currently on the market. Compared to online material, it has the benefit of material being presented in one coherent sequence. Author utilizes many years of teaching experience to communicate an effective way for teaching JavaScript quickly.

This book from Jürgen Claus is a milestone among the books dedicated to the planet sea A knowledgeable overview of marine architectures from both the Pacific and Atlantic regions Discusses the seascape as a fluid studio for visual artists

Stopping Losses from Accidental and Malicious Actions Around the world, users cost organizations billions of dollars due to simple errors and malicious actions. They believe that there is some deficiency in the users. In response, organizations believe that they have to improve their awareness efforts and making more secure users. This is like saying that coalmines should get healthier canaries. The reality is that it takes a multilayered approach that acknowledges that users will inevitably make mistakes or have malicious intent, and the failure is in not planning for that. It takes a holistic approach to assessing risk combined with technical defenses and countermeasures layered with a security culture and continuous improvement. Only with this kind of defense in depth can organizations hope to prevent the worst of the cybersecurity breaches and other user-initiated losses. Using lessons from tested and proven disciplines like military kill-chain analysis, counterterrorism analysis, industrial safety programs, and more, Ira Winkler and Dr. Tracy Celaya's You CAN Stop Stupid provides a methodology to analyze potential losses and determine appropriate countermeasures to implement.  Minimize business losses associated with user failings Proactively plan to prevent and mitigate data breaches Optimize your security spending Cost justify your security and loss reduction efforts Improve your organization’s culture Business technology and security professionals will benefit from the information provided by these two well-known and influential cybersecurity speakers and experts.

ARTIFICIAL INTELLIGENCE (AI) IN FORENSIC SCIENCES Foundational text for teaching and learning within the field of Artificial Intelligence (AI) as it applies to forensic science Artificial Intelligence (AI) in Forensic Sciences presents an overview of the state-of-the-art applications of Artificial Intelligence within Forensic Science, covering issues with validation and new crimes that use AI; issues with triage, preselection, identification, argumentation and explain ability; demonstrating uses of AI in forensic science; and providing discussions on bias when using AI. The text discusses the challenges for the legal presentation of AI data and interpretation and offers solutions to this problem while addressing broader practical and emerging issues in a growing area of interest in forensics. It builds on key developing areas of focus in academic and government research, providing an authoritative and well-researched perspective. Compiled by two highly qualified editors with significant experience in the field, and part of the Wiley — AAFS series ‘Forensic Science in Focus’, Artificial Intelligence (AI) in Forensic Sciences includes information on: Cyber IoT, fundamentals on AI in forensic science, speaker and facial comparison, and deepfake detection Digital-based evidence creation, 3D and AI, interoperability of standards, and forensic audio and speech analysis Text analysis, video and multimedia analytics, reliability, privacy, network forensics, intelligence operations, argumentation support in court, and case applications Identification of genetic markers, current state and federal legislation with regards to AI, and forensics and fingerprint analysis Providing comprehensive coverage of the subject, Artificial Intelligence (AI) in Forensic Sciences is an essential advanced text for final year undergraduates and master’s students in forensic science, as well as universities teaching forensics (police, IT security, digital science and engineering), forensic product vendors and governmental and cyber security agencies.

Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying the package development philosophy used in the package known as the tidyverse (and beyond). In the process, you'll work with devtools, usethis, roxygen2, and testthat, a set of R packages that automate common development tasks. Ideal for developers and data scientists, this book gets you creating packages ASAP, then shows you how to get progressively better over time. You'll learn to focus on what you want your package to do, rather than thinking about package structure. Learn the key components of an R package, including code, documentation, and tests. Get tips on good style, such as organizing functions into files. Streamline your development process with usethis, devtools, and RStudio. Create high quality packages by combining unit tests and continuous integration on GitHub. Maximize your chances of a positive CRAN submission. Turn your existing documentation into a beautiful and user friendly website with pkgdown.

A 2021 ‘BOOK TO LOOK OUT FOR’ – THE INDEPENDENT ‘A mouthpiece for our anxieties and a tonic for our hearts.’ Charly Cox ‘Funny and honest.’ Pandora Sykes ‘Offers readers of all stripes and ages a great overview of relationships in the digital era’. Matt Haig In Millennial Love journalist Olivia Petter explores the questions, quirks and anxieties that consume the contemporary dating landscape. Olivia scrutinises the myths surrounding modern romance and asks why, despite having endless technology designed to aid communication, it’s harder to meet someone now than ever before. The book is based on the Independent’s chart-topping podcast of the same name and expands on some of the issues discussed on the show, including why contraception is a feminist issue, how dating apps have altered our understanding of attraction, and how 'Love Island' became the unlikely lens through which the consequences of so many of these things were exposed. Other topics covered include read receipt anxiety, why we need to rethink our relationship with porn, and the significance of ‘sliding into someone’s DMs’. By combining memoir with social commentary and insights from former podcast guests, including Munroe Bergdorf, Elizabeth Day and Lisa Taddeo, Millennial Love is an essential handbook on what it means to love today.

Stochastic modeling is a set of quantitative techniques for analyzing practical systems with random factors. This area is highly technical and mainly developed by mathematicians. Most existing books are for those with extensive mathematical training; this book minimizes that need and makes the topics easily understandable. Fundamentals of Stochastic Models offers many practical examples and applications and bridges the gap between elementary stochastics process theory and advanced process theory. It addresses both performance evaluation and optimization of stochastic systems and covers different modern analysis techniques such as matrix analytical methods and diffusion and fluid limit methods. It goes on to explore the linkage between stochastic models, machine learning, and artificial intelligence, and discusses how to make use of intuitive approaches instead of traditional theoretical approaches. The goal is to minimize the mathematical background of readers that is required to understand the topics covered in this book. Thus, the book is appropriate for professionals and students in industrial engineering, business and economics, computer science, and applied mathematics.

This unique textbook presents a course on computational linear algebra. Offers many unique applications. MATLAB is used throughout.

This book elaborates fuzzy machine and deep learning models for single class mapping from multi-sensor, multi-temporal remote sensing images while handling mixed pixels and noise. It also covers the ways of pre-processing and spectral dimensionality reduction of temporal data. Further, it discusses the ‘individual sample as mean’ training approach to handle heterogeneity within a class. The appendix section of the book includes case studies such as mapping crop type, forest species, and stubble burnt paddy fields. Key features: Focuses on use of multi-sensor, multi-temporal data while handling spectral overlap between classes Discusses range of fuzzy/deep learning models capable to extract specific single class and separates noise Describes pre-processing while using spectral, textural, CBSI indices, and back scatter coefficient/Radar Vegetation Index (RVI) Discusses the role of training data to handle the heterogeneity within a class Supports multi-sensor and multi-temporal data processing through in-house SMIC software Includes case studies and practical applications for single class mapping This book is intended for graduate/postgraduate students, research scholars, and professionals working in environmental, geography, computer sciences, remote sensing, geoinformatics, forestry, agriculture, post-disaster, urban transition studies, and other related areas.

Provides background material needed to understand digital twin technology Presents computational facet of digital twin Includes physics based and surrogate model representations Addresses the problem of uncertainty in measurements and modeling Discusses practical case studies of implementation of digital twins addressing additive manufacturing, server farms, predictive maintenance, and smart cities

A robust and engaging account of the single greatest threat faced by AI and ML systems In Not With A Bug, But With A Sticker: Attacks on Machine Learning Systems and What To Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour – from inside secretive government organizations to academic workshops at ski chalets to Google’s cafeteria – recounting how major AI systems remain vulnerable to the exploits of bad actors of all stripes. Based on hundreds of interviews of academic researchers, policy makers, business leaders and national security experts, the authors compile the complex science of attacking AI systems with color and flourish and provide a front row seat to those who championed this change. Grounded in real world examples of previous attacks, you will learn how adversaries can upend the reliability of otherwise robust AI systems with straightforward exploits. The steeplechase to solve this problem has already begun: Nations and organizations are aware that securing AI systems brings forth an indomitable advantage: the prize is not just to keep AI systems safe but also the ability to disrupt the competition’s AI systems. An essential and eye-opening resource for machine learning and software engineers, policy makers and business leaders involved with artificial intelligence, and academics studying topics including cybersecurity and computer science, Not With A Bug, But With A Sticker is a warning—albeit an entertaining and engaging one—we should all heed. How we secure our AI systems will define the next decade. The stakes have never been higher, and public attention and debate on the issue has never been scarcer. The authors are donating the proceeds from this book to two charities: Black in AI and Bountiful Children’s Foundation.