Computer science Books

Book SynopsisGain the necessary technical skills, tools, and insights to succeed in the crypto working environment. Changing market conditions have created new opportunities and working conditions. This book goes beyond just getting a job, as it shares a myriad of hidden tips on how to thrive within this constantly evolving ecosystem. Through examples and detailed typologies, you'll work out which crypto job is the best fit for you. You'll begin by reviewing some fun facts and anecdotes illustrating life in a Web3 environment, with a careful examination of the various roles in crypto, blockchain, and digital assets. You'll then compare roles in the traditional corporate and financial environments with those in the crypto world from a risk and reward perspective. From there you'll prepare for crypto job interviews with a focus on what to expect and fine-tuning the necessary expertise to excel. Different types of contracts, the onboarding process, communication tools, the intricacies of video conferences, internal storage, and various crypto-specific operational skills will all be clearly explained as well. So You Want to Work in Crypto provides all the strategies you'll need to stay ahead of the curve in the ever-changing crypto world. What You'll LearnExamine what job positions exist in Web3 and how to obtain the right one for you. Prepare yourself for the Web3 environment and the type of job you will get. See how to strategically evolve your career in the world of crypto. Who This Book Is ForAny individual curious about evolving their career, obtaining their first job, or simply looking to find a new, more fulfilling job in an exciting revolutionary industry.

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Book SynopsisTake a deep dive into the intricacies of launching and successfully managing a cryptocurrency token. This book is an indispensable resource, providing invaluable insights and practical advice. Spanning 12 chapters, the book begins with the fundamentals, explaining the different types of tokens and the core concepts of crypto projects, guiding readers through the critical decision-making process about the necessity and role of a token in their venture. As the narrative progresses, you are taken on a journey through the lifecycle of a crypto project. It emphasizes the importance of a well-thought-out roadmap, a compelling pitch deck, and the crucial process of assembling a skilled team. Diving deeper, the book explores the complex world of tokenomics, reviewing the various economic models behind tokens and how to tailor them to specific projects. A key aspect of this guide is its focus on go-to-market strategies, including targeting the right audience, effective marketing techniques, and the vital role of community building. Additionally, it addresses the essentials of fundraising in the crypto space, highlighting the types of investors to approach and strategies for engaging them effectively. Security and stability are paramount in the crypto world. The book provides a detailed analysis of the storage and custody of funds, comparing centralized and decentralized mechanisms and emphasizing the importance of robust security measures. This is crucial for ensuring liquidity and accessibility of the token in the market. The guide culminates with a focus on the launch day, detailing the preparation, organization, and key considerations to ensure a successful token launch. When done you'll be well-equipped to navigate the complex and exciting world of cryptocurrency token launches. What You'll LearnDevelop a successful launch strategy for a token. Prepare the decks and documents for a successful token campaign. Discover negotiation tactics required to reduce fees for all your counterparts. Explore techniques required to maintain the health and popularity of your token. Who This Book Is ForThose considering launching a token, companies looking to tokenize assets, accelerators and incubators, advisors and blockchain teachers/professors, and crypto firms as part of their onboarding material.

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Book SynopsisAnalyse how AI and other cutting-edge technologies affect the complex web of international financial transactions. The global remittance sector and artificial intelligence (AI) work together in a way that is testament to the revolutionary force of innovation in the always changing financial and technology landscape. As we stand at the threshold of a new age, this book aims to explore the layers of complexity underlying the confluence of AI and remittances. Your investigation will go beyond the current state of affairs and into the future, whereby predictive analytics and autonomous financial transactions will fundamentally alter the way that we send and receive money internationally. This process's incorporation of AI technology represents a revolution rather than a simple progression, one that might improve millions of people's lives by streamlining, securing, and lowering the cost of financial transactions. This book breaks down the complex workings of AI prediction models, reveals how blockchain integration may be used to facilitate safe and transparent transactions, and examines how biometric authentication can strengthen the security of financial transactions. It dives into the complexities of regulatory compliance, understanding the difficult balance between innovation and conformity to existing standards. When machines carry out transactions based on complex algorithms and current market circumstances, what does it entail for people and economies? What effect does this change have on how people make financial decisions? This book is an invitation to imagine a future in which financial systems are not just efficient but also naturally intelligent. It is a call to reflect on the moral ramifications, the effects on society, and the obligations that accompany the dawn of a new era of financial opportunity. Remittances are about to undergo a revolution, and you have a crucial role to play in determining how this will play out. What You'll LearnUnderstand the integration of AI and other technology in remittancesto enhance efficiency, security, and cost-effectiveness of cross-border financial transactions. Examine the impact of AI-driven cross border flows on global economic development, particularly in communities heavily reliant on remittances. Investigate the social benefits and potential challenges posed by AI in maintaining or altering familial and community ties through remittance flowsCritically evaluate regulatory and ethical challenges while fostering innovation and adhering to existing financial laws and standards. Explore future scenarios whereAI governs autonomous financial transactions andthe role of humans in an AI-driven financial ecosystem. Debate how such changes might redefine personal and communal financial interactions. Who This Book Is ForFinTech practitioners, Finance students, professionals in working in Payments and/or Remittances

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Book SynopsisThis book examines contemporary structural social injustices from a feminist perspective. It asks: what makes oppression, discrimination, and domination wrongful? Is there a single wrongness-making feature of various social injustices that are due to social kind membership? Why is sexist oppression of women wrongful? What does the wrongfulness of patriarchal damage done to women consist in? In thinking about what normatively grounds social injustice, the book puts forward two related views. First, it argues for a paradigm shift in focus away from feminist philosophy that is organized around the gender concept woman, and towards feminist philosophy that is humanist. This is against the following theoretical backdrop: Politically effective feminism requires ways to elucidate how and why patriarchy damages women, and to articulate and defend feminism''s critical claims. In order to meet these normative demands an influential theoretical outlook has emerged: for emancipatory purposes feminTrade ReviewTaken as a whole, the monograph is an outstanding contribution to feminist philosophical scholarship, and one that I anticipate will alter the course of a number of discussions in this field in fruitful ways. * Katharine Jenkins, University of Nottingham, Mind *Mari Mikkola's The Wrong of Injustice is a tour de force that combines a critique of recent philosophical debates about the notion of gender with an argument that feminist philosophy should adopt a "humanist" normative position rather than a specifically feminist one. ... The book is an important and ambitious contribution to feminist philosophy and deserves to be studied by both specialists and students. It would be ideal for an advanced undergraduate or graduate seminar owing to its careful exposition and critique of many of the main themes within contemporary feminist philosophy. ... Mikkola's book displays an impressive breadth of research and a multitude of dense, detailed arguments. ... It displays a mastery of diverse philosophical literatures from feminist metaphysics to the (not necessarily feminist) social philosophy of discrimination, domination, and oppression. * Natalie Stoljar, Ethics *Mikkola's book The Wrong of Injustice undertakes a bold paradigm shift in feminist philosophy. She has provided oodles of arguments to support it; but also, as in any paradigm shift, the real power of the work comes from clearing space for new and enlightening ways of thinking. There are many of us looking for non-ideal theory--not just non-ideal commitments--to guide the normative dimension of our work. Mikkola's book provides a model, in fact, a landmark, to guide us as we move ahead. * Sally Haslanger, Massachusetts Institute of Technology *Mikkola's book is a powerful and original argument for neo-humanist feminism. * Charlotte Witt, University of New Hampshire *Table of ContentsChapter 1: Dehumanization as the Wrong of Social Injustice 1.1. Introduction 1.2. Against the Gender Controversy 1.3. Going Beyond Gender: Humanist Feminism 1.4. Methodological Commitments 1.5. Structure of the Book Part I: Against the Gender Controversy Chapter 2: The Gender Controversy 2.1. Biological Determinism and Gender Terminology 2.2. Gender Construction 2.3. Uniformity of Gender 2.4. Sex Classification 2.5.Usefulness of the Sex/Gender Distinction 2.6. Women as a Social Kind Chapter 3: Nominalist Responses to the Semantic and Ontological Puzzles 3.1. The 'Positive' Category of Women 3.2. Women as a Social Series 3.3. Unity, Normativity, and Oppression 3.4. Women as a Resemblance Class 3.4.1. Tenability of Gender Realism 3.4.2. Plausibility of Resemblance Nominalism Chapter 4: Realist Responses to the Semantic and Ontological Puzzles 4.1. Women as FMP-Category 4.2. Social Subordination and Privilege as Marks of Gender 4.2.1. Ameliorative Analysis of woman 4.2.2. Benefits of the Revisionary Analysis 4.3. Gendered Social Identity as Positionality 4.4. Historical Essentialism 4.4.1. Gender as a Natural Kind 4.4.2. Feminist Politics and Historical Essentialism 4.5. Upshot of the Discussion Chapter 5: Deflating the Puzzles 5.1. Deflating the Semantic Puzzle 5.2. Deflating the Ontological Puzzle 5.2.1. Conventionalism is Unintuitive 5.2.2. The Abolitionist Implication is Undesirable 5.2.3. The Trait/ Norm Covariance Model 5.2.4. Ontological Commitments, and the Trait/ Norm Covariance Model 5.3. The Gender Controversy Deflated Part II: Normativity Anew Chapter 6: Dehumanization 6.1. Introduction 6.2. Why Humanism 6.3. Rape as Dehumanizing 6.3.1. The Objectification Argument 6.3.2. The 'Soul Murder' Argument 6.4. Dehumanization in General 6.4.1. Our Legitimate Interests 6.4.2. Moral Injury 6.5. Dehumanization and Feminism Chapter 7: Forms of Injustice and Emancipatory Social Theory 7.1. Introduction 7.2. Emancipatory Social Theory: Desiderata 7.3. Forms of Injustice 7.3.1. Discrimination 7.3.2. Domination 7.3.3. Oppression: A First-Stab 7.3.4. Oppression: A Second-Stab Chapter 8: Contours of Injustice and Feminist Social Theory 8.1. Introduction 8.2. Contours of Injustice 8.3. Feminist Social Theory and Dehumanization 8.4. The Argument So Far Chapter 9: Overcoming Dehumanization 9.1. Freedom 9.2. Human Flourishing 9.3. Equality 9.3.1. The Basic Picture 9.3.2. Objections and Clarifications 9.3.3. Democratic Equality 9.4. Humanist Feminism: Final Remarks Bibliography

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Book SynopsisThis book discusses the evolution of security and privacy issues and brings related technological tools, techniques, and solutions into one single source. The book will take readers on a journey to understanding the security issues and possible solutions involving various threats, attacks, and defense mechanisms, which include IoT, cloud computing, Big Data, lightweight cryptography for blockchain, and data-intensive techniques, and how it can be applied to various applications for general and specific use. Graduate and postgraduate students, researchers, and those working in this industry will find this book easy to understand and use for security applications and privacy issues.

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Book SynopsisWith the widespread transformation of information into digital form throughout society â firms and organisations are embracing this development to adopt multiple types of IT to increase internal efficiency and to achieve external visibility and effectiveness â we have now reached a position where there is data in abundance and the challenge is to manage and make use of it fully. This book addresses this new managerial situation, the post-digitalisation era, and offers novel perspectives on managing the digital landscape.The topics span how the post-digitalisation era has the potential to renew organisations, markets and society. The chapters of the book are structured in three topical sections but can also be read individually. The chapters are structured to offer insights into the developments that take place at the intersection of the management, information systems and computer science disciplines. It features more than 70 researchers and managers as collaborating authors Table of ContentsPrefacePeter Ekman, Peter Dahlin and Christina KellerForewordFredrik Nilsson and Fredrik Tell1. Perspectives on Management and Information Technology after Digital Transformation Peter Ekman, Peter Dahlin and Christina Keller2. Digital Transformation: Towards a New Perspective for Large Established Organisations in a Digital Age Alan W. BrownPart 1 – The transformation of society and markets3. Managing Digital Servitization: A Service Ecosystem PerspectiveDavid Sörhammar, Bård Tronvoll and Christian Kowalkowski4. Caught on the platform or jumping onto the digital train: Challenges for industries lagging behind in digitalisationPeter Ekman, Magnus Berglind and Steven Thompson5. Digitalisation for Sustainability: Conceptualisation, Implications and Future Research Directions Elena Anastasiadou, Linda Alkire and Jimmie Röndell6. Reaching New Heights in the Cloud: The Digital Transformation of the Video Games Industry Kevin Walther and David Sörhammar7. Hyper-Taylorism and Third-order Technologies: Making Sense of the Transformation of Work and Management in a Post-digital Era Christoffer Andersson, Lucia Crevani, Anette Hallin, Caroline Ingvarsson, Chris Ivory, Inti José Lammi, Eva Lindell, Irina Popova and Anna Uhlin8. Why Space is Not Enough: Service innovation and service delivery in senior housingPetter Ahlström, Göran Lindahl, Markus Fellesson, Börje Bjelke and Fredrik Nilsson9. Challenges in Implementing Digital Assistive Technology in Municipal HealthcareAnn Svensson, Linda Bergkvist, Charlotte Bäccman and Susanne DurstPart 2 – Managerial and organisational challenges10. Modern project management: Challenges for the future Klas Sundberg, Birger Rapp and Christina Keller11. Managing the Paradoxes of Digital Product InnovationFredrik Svahn and Bendik Bygstad12. When External Reporting Goes Social: New Conditions for Transparency and Accountability?Cecilia Gullberg13. Robotic Process Automation and the Accounting Profession’s Extinction ProphecyMatthias Holmstedt, Fredrik Jeanson and Angelina Sundström14. Managing Digital Employee-Driven Innovation: The Role of Middle-Level Managers and Ambidextrous LeadershipIzabelle Bäckström and Peter Magnusson15. Digital Gamification of Organisational Functions and Emergent Management PracticesEdward Gillmore16. Leveraging Digital Technologies in Enterprise Risk ManagementJason Crawford and Jan LindvallSection 3 – Framing digitalisation17. The End of Business Intelligence and Business AnalyticsMatthias Holmstedt and Peter Dahlin18. ‘Deleted User’: Signalling Digital Disenchantment in the Post-Digital SocietyCristina Ghita, Claes Thorén and Martin Stojanov19. The Role of Boundary-Spanners in the Post-Digitalised Multinational CorporationHenrik Dellestrand, Olof Lindahl and Jakob Westergren20. The Effect of Digital Transformation on Subsidiary Influence in the Multinational EnterpriseNoushan Memar, Ulf Andersson, Peter Dahlin and Peter Ekman21. Understanding Information System Outsourcing in the Digital Transformation Era: The Business-relationship Triad ViewCecilia Erixon and Peter Thilenius22. Transforming the Management/Profession Divide: The Use of the Red–Green Matrix in Swedish SchoolsAnton Borell, Johan Klaassen, Roland Almqvist and Jan Löwstedt23. Integrating research in master’s programmes: Developing students’ skills to embrace digitally transformed marketsTodd Drennan, Cecilia Thilenius Lindh and Emilia Rovira NordmanIndex

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Book SynopsisThis book focuses on the intelligent technologies that are transforming creative practices and industries.The future of creative work will be more complicated than âœthe robots will take our jobs.â The workplace is becoming increasingly hybridized, with human and computational labor complementing each other. Some economic roles for the former will no doubt fade over time, while new roles are created to produce artificial intelligence (AI)-related technologies and implementations for productivity. New tools for the generation and personalization of content across platforms will be as ubiquitous as the automation of repetitive tasks in content creation workflows. Cultural conceptions of what it means to be a creative worker will necessarily change as a result of these transformations in human-machine labor. The volume covers the possibilities of humans and robots developing collegial relationships, creative cybernetics as machines and artists become co-creators of art, the reco

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Book SynopsisDiscrete structures, like DNA sequences and the internet, are complex objects created from indivisible parts. Now more accessible to graduate students, this book introduces multivariate generating functions, which are used to create computational tools to detect and understand patterns in such structures.Trade Review'A definitive treatment of a challenging but very useful subject. There is a wide variety of situations calling for the estimation of the coefficients of a multivariate generating function. The authors have done a superb job of classifying and elucidating the myriad of available techniques for achieving this aim.' Richard P. Stanley, University of Miami'This book is an invaluable resource that is certain to have dramatic impact on research and teaching in this rapidly developing area of mathematics. The first edition broke new ground; this edition prepares the field for others to harvest new knowledge with important applications in many scientific disciplines.'Table of ContentsPart I. Combinatorial Enumeration: 1. Introduction; 2. Generating functions; 3. Univariate asymptotics; Part II. Mathematical Background: 4. Fourier–Laplace integrals in one variable; 5. Multivariate Fourier–Laplace integrals; 6. Laurent series, amoebas, and convex geometry; Part III. Multivariate Enumeration: 7. Overview of analytic methods for multivariate generating functions; 8. Effective computations and ACSV; 9. Smooth point asymptotics; 10. Multiple point asymptotics; 11. Cone point asymptotics; 12. Combinatorial applications; 13. Challenges and extensions; Appendices: A. Integration on manifolds; B. Algebraic topology; C. Residue forms and classical Morse theory; D. Stratification and stratified Morse theory; References; Author index; Subject index.

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Book SynopsisVirtual Humans provides a much-needed definition of what constitutes a virtual human' and places virtual humans within the wider context of Artificial Intelligence development. It explores the technical approaches to creating a virtual human, as well as emergent issues such as embodiment, identity, agency and digital immortality, and the resulting ethical challenges. The book presents an overview of current research and practice in this area, and outlines the major challenges faced by today's developers and researchers. The book examines the possibility for using virtual humans in a variety of roles, from personal assistants to teaching, coaching and knowledge management, and the book situates these discussions around familiar applications (e.g. Siri, Cortana, Alexa) and the portrayal of virtual humans within Science Fiction.Features Presents a comprehensive overview of this rapidly developing field Provides anTrade Review"This book presents an overview of the present state of play with virtual humans. Appearance, attributes, communication and intelligence are all investigated, and the architectures involved are covered in detail. If you have little knowledge of what a virtual human is, but want to find out, then this is the book for you. For researchers in the virtual human field this is a definite must." -Professor Kevin Warwick, Coventry University "David Burden and Maggi Savin-Baden’s Virtual Humans offers a thorough, research-based treatment of how digital entities with human-like features and capabilities have left the domain of science fiction and are rapidly becoming a major aspect of human culture. In their clearly-written and well-organized work, they describe the current forms and abilities of virtual humans (including smart speakers and virtual assistant systems like Siri, Alexa, and Cortana and various types of Internet-based chatbots); examine how the creation of virtual bodies, senses, and minds can be combined to create virtual humans; and consider potential developments in the nature and functionality of virtual agents across a range of timeframes from the end of the next decade to the end of the century. Significantly, the authors recognize and discuss the great ethical, moral and social implications of these technological developments which makes their work relevant and important for the social sciences and humanities as well as the domains of computing and information sciences. I certainly intend to use Virtual Humans as an assigned reading in the interdisciplinary courses I teach on the personal and social impact of leading-edge digital technologies." -Richard Gilbert, Professor of Psychology and Director of the Psychology and New Technology Research Lab, Loyola Marymount University, Los Angeles, California "Intelligent, pragmatic and insightful, Virtual Humans is an essential guide for those who want to understand the complex landscape of today’s technology when thinking about designing and building a virtual human. Helpfully, it clearly deploys a wealth of supporting analysis, case studies, research, ethical questions, and moral dilemmas and adds a refreshing dose of healthy common sense along the way." -Nicola Strong, Strong Enterprises Table of ContentsIntroduction Part I The Landscape Chapter 1 What are Virtual Humans? Chapter 2 Virtual Humans and Artificial Intelligence Part II Technology Chapter 3 Body and Senses Chapter 4 Mind Chapter 5 Communication Chapter 6 Architecture Chapter 7 Embodiment Chapter 8 Assembling and Assemblages Part III Identity Chapter 9 Digital Ethics Chapter 10 Identity and Agency Chapter 11 Virtual Humans for Education Chapter 12 Digital Immortality Chapter 13 Futures and Possibilities Glossary

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Book SynopsisAs the title suggests, this book explores the concepts of drawing, graphics and animation in the context of coding. In this endeavour, in addition to initiating the process with some historical perspectives on programming languages, it prides itself by presenting complex concepts in an easy-to-understand fashion for students, artists, hobbyists as well as those interested in computer science, computer graphics, digital media, or interdisciplinary studies.Being able to code requires abstract thinking, mathematics skills, spatial ability, logical thinking, imagination, and creativity. All these abilities can be acquired with practice, and can be mastered by practical exposure to art, music, and literature. This book discusses art, poetry and other forms of writing while pondering difficult concepts in programming; it looks at how we use our senses in the process of learning computing and programming.Features: Introduces coding in a visual way Explores Table of ContentsIntroduction Introduction to Coding Coding for Art Interactivity and visualising inputs: mouse, data, finger Translation Conclusions and Educational Propositions Glossary

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Book SynopsisOffers an overview of the state-of-the-art and emerging themes in affective computing, including a comprehensive review of the existing approaches to affective computing systems and social signal processing. The book provides in-depth case studies of applied affective computing in various domains, such as social robotics and mental well-being.

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Book SynopsisBuild real-world time series forecasting systems which scale to millions of time series by applying modern machine learning and deep learning concepts Key Features Explore industry-tested machine learning techniques used to forecast millions of time series Get started with the revolutionary paradigm of global forecasting models Get to grips with new concepts by applying them to real-world datasets of energy forecasting Book DescriptionWe live in a serendipitous era where the explosion in the quantum of data collected and a renewed interest in data-driven techniques such as machine learning (ML), has changed the landscape of analytics, and with it, time series forecasting. This book, filled with industry-tested tips and tricks, takes you beyond commonly used classical statistical methods such as ARIMA and introduces to you the latest techniques from the world of ML. This is a comprehensive guide to analyzing, visualizing, and creating state-of-the-art forecasting systems, complete with common topics such as ML and deep learning (DL) as well as rarely touched-upon topics such as global forecasting models, cross-validation strategies, and forecast metrics. You’ll begin by exploring the basics of data handling, data visualization, and classical statistical methods before moving on to ML and DL models for time series forecasting. This book takes you on a hands-on journey in which you’ll develop state-of-the-art ML (linear regression to gradient-boosted trees) and DL (feed-forward neural networks, LSTMs, and transformers) models on a real-world dataset along with exploring practical topics such as interpretability. By the end of this book, you’ll be able to build world-class time series forecasting systems and tackle problems in the real world.What you will learn Find out how to manipulate and visualize time series data like a pro Set strong baselines with popular models such as ARIMA Discover how time series forecasting can be cast as regression Engineer features for machine learning models for forecasting Explore the exciting world of ensembling and stacking models Get to grips with the global forecasting paradigm Understand and apply state-of-the-art DL models such as N-BEATS and Autoformer Explore multi-step forecasting and cross-validation strategies Who this book is forThe book is for data scientists, data analysts, machine learning engineers, and Python developers who want to build industry-ready time series models. Since the book explains most concepts from the ground up, basic proficiency in Python is all you need. Prior understanding of machine learning or forecasting will help speed up your learning. For experienced machine learning and forecasting practitioners, this book has a lot to offer in terms of advanced techniques and traversing the latest research frontiers in time series forecasting.Table of ContentsTable of Contents Introducing Time Series Acquiring and Processing Time Series Data Analyzing and Visualizing Time Series Data Setting a Strong Baseline Forecast Time Series Forecasting as Regression Feature Engineering for Time Series Forecasting Target Transformations for Time Series Forecasting Forecasting Time Series with Machine Learning Models Ensembling and Stacking Global Forecasting Models Introduction to Deep Learning Building Blocks of Deep Learning for Time Series Common Modeling Patterns for Time Series Attention and Transformers for Time Series Strategies for Global Deep Learning Forecasting Models Specialized Deep Learning Architectures for Forecasting Multi-Step Forecasting Evaluating Forecasts – Forecast Metrics Evaluating Forecasts – Validation Strategies

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Book SynopsisDemystify causal inference and casual discovery by uncovering causal principles and merging them with powerful machine learning algorithms for observational and experimental data Purchase of the print or Kindle book includes a free PDF eBook Key Features Examine Pearlian causal concepts such as structural causal models, interventions, counterfactuals, and more Discover modern causal inference techniques for average and heterogenous treatment effect estimation Explore and leverage traditional and modern causal discovery methods Book DescriptionCausal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that elude a purely statistical mindset. Causal Inference and Discovery in Python helps you unlock the potential of causality. You’ll start with basic motivations behind causal thinking and a comprehensive introduction to Pearlian causal concepts, such as structural causal models, interventions, counterfactuals, and more. Each concept is accompanied by a theoretical explanation and a set of practical exercises with Python code. Next, you’ll dive into the world of causal effect estimation, consistently progressing towards modern machine learning methods. Step-by-step, you’ll discover Python causal ecosystem and harness the power of cutting-edge algorithms. You’ll further explore the mechanics of how “causes leave traces” and compare the main families of causal discovery algorithms. The final chapter gives you a broad outlook into the future of causal AI where we examine challenges and opportunities and provide you with a comprehensive list of resources to learn more.What you will learn Master the fundamental concepts of causal inference Decipher the mysteries of structural causal models Unleash the power of the 4-step causal inference process in Python Explore advanced uplift modeling techniques Unlock the secrets of modern causal discovery using Python Use causal inference for social impact and community benefit Who this book is forThis book is for machine learning engineers, data scientists, and machine learning researchers looking to extend their data science toolkit and explore causal machine learning. It will also help developers familiar with causality who have worked in another technology and want to switch to Python, and data scientists with a history of working with traditional causality who want to learn causal machine learning. It’s also a must-read for tech-savvy entrepreneurs looking to build a competitive edge for their products and go beyond the limitations of traditional machine learning.Table of ContentsTable of Contents Causality – Hey, We Have Machine Learning, So Why Even Bother? Judea Pearl and the Ladder of Causation Regression, Observations, and Interventions Graphical Models Forks, Chains, and Immoralities Nodes, Edges, and Statistical (In)dependence The Four-Step Process of Causal Inference Causal Models – Assumptions and Challenges Causal Inference and Machine Learning – from Matching to Meta-Learners Causal Inference and Machine Learning – Advanced Estimators, Experiments, Evaluations, and More Causal Inference and Machine Learning – Deep Learning, NLP, and Beyond Can I Have a Causal Graph, Please? Causal Discovery and Machine Learning – from Assumptions to Applications Causal Discovery and Machine Learning – Advanced Deep Learning and Beyond Epilogue

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Book SynopsisUnlock the true potential of software testing to achieve seamless software performance with this comprehensive guide Key Features Gain a solid understanding of software testing and master its multifaceted strategies Empower yourself to effectively overcome software testing challenges Develop actionable real-world testing skills for succeeding in any role Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionSoftware Testing Strategies covers a wide range of topics in the field of software testing, providing practical insights and strategies for professionals at every level. With equal emphasis on theoretical knowledge and practical application, this book is a valuable resource for programmers, testers, and anyone involved in software development. The first part delves into the fundamentals of software testing, teaching you about test design, tooling, and automation. The chapters help you get to grips with specialized testing areas, including security, internationalization, accessibility, and performance. The second part focuses on the integration of testing into the broader software delivery process, exploring different delivery models and puzzle pieces contributing to effective testing. You’ll discover how to craft your own test strategies and learn about lean approaches to software testing for optimizing processes. The final part goes beyond technicalities, addressing the broader context of testing. The chapters cover case studies, experience reports, and testing responsibilities, and discuss the philosophy and ethics of software testing. By the end of this book, you’ll be equipped to elevate your testing game and ensure software quality, and have an indispensable guide to the ever-evolving landscape of software quality assurance.What you will learn Explore accessibility, functional testing, performance testing, and more as an integral part of testing Find out how to implement a wide range of testing approaches Develop the skills needed to create effective testing strategies tailored to your project's needs Discover how to prioritize and execute the most impactful test ideas Gain insight into when and how to apply different testing elements Defend your chosen testing strategy with a comprehensive understanding of its components Who this book is forThis book is for a broad spectrum of professionals engaged in software development, including programmers, testers, and DevOps specialists. Tailored to those who aspire to elevate their testing practices beyond the basics, the book caters to anyone seeking practical insights and strategies to master the nuanced interplay between human intuition and automation. Whether you are a seasoned developer, meticulous tester, or DevOps professional, this comprehensive guide offers a transformative roadmap to become an adept strategist in the dynamic realm of software quality assurance.Table of ContentsTable of Contents Testing and Designing Tests Fundamental Issues in Tooling and Automation Programmer-Facing Testing Customer-Facing Tests Specialized Testing Testing Related Skills Test Data Management Delivery Models and Testing The Puzzle Pieces of Good Testing Putting Your Test Strategy Together Lean Software Testing Case Studies and Experience Reports Testing Activities or a Testing Role? Philosophy and Ethics in Software Testing Words and Language About Work Testing Strategy Applied

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Book SynopsisHarness the powerful Python programming language to navigate the realms of geographic information systems, remote sensing, topography, and more, while embracing a guiding framework for effective geospatial analysis Key Features Create GIS solutions using the new features introduced in Python 3.10 Explore a range of GIS tools and libraries, including PostGIS, QGIS, and PROJ Identify the tools and resources that best align with your specific needs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionGeospatial analysis is used in almost every domain you can think of, including defense, farming, and even medicine. In this special 10th anniversary edition, you'll embark on an exhilarating geospatial analysis adventure using Python. This fourth edition starts with the fundamental concepts, enhancing your expertise in geospatial analysis processes with the help of illustrations, basic formulas, and pseudocode for real-world applications. As you progress, you’ll explore the vast and intricate geospatial technology ecosystem, featuring thousands of software libraries and packages, each offering unique capabilities and insights. This book also explores practical Python GIS geospatial applications, remote sensing data, elevation data, and the dynamic world of geospatial modeling. It emphasizes the predictive and decision-making potential of geospatial technology, allowing you to visualize complex natural world concepts, such as environmental conservation, urban planning, and disaster management to make informed choices. You’ll also learn how to leverage Python to process real-time data and create valuable information products. By the end of this book, you'll have acquired the knowledge and techniques needed to build a complete geospatial application that can generate a report and can be further customized for different purposes.What you will learn Automate geospatial analysis workflows using Python Understand the different formats in which geospatial data is available Unleash geospatial tech tools to create stunning visualizations Create thematic maps with Python tools such as PyShp, OGR, and the Python Imaging Library Build a geospatial Python toolbox for analysis and application development Unlock remote sensing secrets, detect changes, and process imagery Leverage ChatGPT for solving Python geospatial solutions Apply geospatial analysis to real-time data tracking and storm chasing Who this book is forThis book is for Python developers, researchers, or analysts who want to perform geospatial modeling and GIS analysis with Python. Basic knowledge of digital mapping and analysis using Python or other scripting languages will be helpful.Table of ContentsTable of Contents Learning about Geospatial Analysis with Python Learning about Geospatial Data The Geospatial Technology Landscape Geospatial Python Toolbox Python and Geospatial Algorithms Creating and Editing GIS Data Python and Remote Sensing Python and Elevation Data Advanced Geospatial Modeling Working with Real-Time Data Putting It All Together

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