Thank You For Joining The Algorithm
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The Skull Laurel 002
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Author : Cameron Howard
language : en
Publisher: Tenebrous Press
Release Date : 2025-01-15
The Skull Laurel 002 written by Cameron Howard and has been published by Tenebrous Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-15 with Fiction categories.
The Skull & Laurel returns with its second issue, packed with an abundance of New Weird Literature for you! Featuring stories from Dmitri Akers, Atalanti Evripidou, Cedrick May, Neal Auch, Le Werner, Anne Liberton, Ria Hill, Beau Farrow, and Jonathan Olfert, and non-fiction from Xochilt Avila.
Thank You For Joining The Algorithm
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Author : Alex Woodroe
language : en
Publisher:
Release Date : 2023-11-15
Thank You For Joining The Algorithm written by Alex Woodroe and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-15 with categories.
THANK YOU FOR JOINING THE ALGORITHM is a collection of Sci-Horror short fiction, comics, poems, and art that celebrates the connection between humanity and creativity in the face of ever-increasing pressure to submit to the inevitability of algorithmic dominion.
The Fair Algorithm Ensuring Fairness In Machine Learning
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Author : S Williams
language : en
Publisher: NFT Publishing
Release Date : 2025-04-15
The Fair Algorithm Ensuring Fairness In Machine Learning written by S Williams and has been published by NFT Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-15 with Computers categories.
In an era where artificial intelligence (AI) plays a pivotal role in shaping decisions across industries, ensuring fairness and eliminating bias in machine learning systems has become more critical than ever. This book dives deep into the pressing challenges of algorithmic fairness , exploring how biases emerge in AI systems and offering actionable strategies to mitigate them. From understanding the roots of data bias and model design flaws to implementing cutting-edge debiasing techniques and fairness metrics , this comprehensive guide equips readers with the tools needed to build ethical, transparent, and inclusive AI. Through real-world case studies from sectors like hiring, lending, healthcare, and law enforcement, the book highlights both failures and successes in achieving equitable outcomes. It examines emerging innovations such as explainable AI (XAI) , bias detection platforms , and fairness-aware algorithms that enhance transparency in AI and foster public trust . Readers will also explore the ethical implications of AI , including debates on privacy, discrimination, and the societal impact of deploying biased algorithms in critical decision-making processes. The narrative further delves into the legal and regulatory frameworks governing AI development, emphasizing the importance of accountability, consumer protection, and adherence to universal values. By applying principles like Kantian ethics to AI practices, the book advocates for responsible AI design that prioritizes inclusivity, equity, and long-term benefits for individuals and communities. Whether you're a developer seeking practical methods to integrate fairness metrics into your workflows or a policymaker navigating regulatory gaps , this resource provides invaluable insights into overcoming barriers such as algorithmic opacity , insufficient diversity in datasets, and resistance to accountability. With a focus on blending empirical evidence with universal ideals, the book concludes with a visionary roadmap toward a future where AI systems are not only fair and transparent but also aligned with ethical principles that uphold human dignity and equality. Packed with knowledge on machine learning ethics , societal inequalities in AI , and innovative trends in fair AI tools, this book is essential reading for anyone committed to building trustworthy, equitable, and impactful AI systems.
Introduction To Algorithms
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Author : Cuantum Technologies LLC
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-06-14
Introduction To Algorithms written by Cuantum Technologies LLC and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-14 with Computers categories.
Discover the fundamentals and advanced concepts of algorithms with this comprehensive course. Learn about efficiency, types, design techniques, and real-world applications, and enhance your algorithmic knowledge. Key Features Basics to advanced algorithm design and applications, along with real-world applications Engaging exercises & case studies from the latest industry trends & practices for reinforcement Clear, step-by-step instructions for complex and advanced topics Book DescriptionBegin your journey into the fascinating world of algorithms with this comprehensive course. Starting with an introduction to the basics, you will learn about pseudocode and flowcharts, the fundamental tools for representing algorithms. As you progress, you'll delve into the efficiency of algorithms, understanding how to evaluate and optimize them for better performance. The course will also cover various basic algorithm types, providing a solid foundation for further exploration. You will explore specific categories of algorithms, including search and sort algorithms, which are crucial for managing and retrieving data efficiently. You will also learn about graph algorithms, which are essential for solving problems related to networks and relationships. Additionally, the course will introduce you to the data structures commonly used in algorithms. Towards the end, the focus shifts to algorithm design techniques and their real-world applications. You will discover various strategies for creating efficient and effective algorithms and see how these techniques are applied in real-world scenarios. By the end of the course, you will have a thorough understanding of algorithmic principles and be equipped with the skills to apply them in your technical career.What you will learn Understand the basics of algorithms and their significance Evaluate the efficiency of different algorithms Apply various types of algorithms to solve complex problems Utilize graph algorithms for network-related issues Implement appropriate data structures for algorithm optimization Design efficient algorithms for real-world applications Who this book is for This course is designed for a wide range of learners, including technical professionals looking to enhance their algorithmic knowledge, computer science students seeking a deeper understanding of algorithm principles, and software developers aiming to improve their coding efficiency. Additionally, it is suitable for data scientists and analysts who need to apply algorithms to data management and analysis tasks, educators looking for comprehensive teaching material on algorithms, and hobbyists interested in expanding their technical skill set.
How To Beat The Facebook Algorithms And Become A Superstar On Facebook
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Author : MR. BIG WEALTH
language : en
Publisher: MR. BIG WEALTH
Release Date : 2023-12-13
How To Beat The Facebook Algorithms And Become A Superstar On Facebook written by MR. BIG WEALTH and has been published by MR. BIG WEALTH this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-13 with Computers categories.
Want to conquer the Facebook algorithm and become a superstar? MR. BIG WEALTH is a 164-page book that reveals secret strategies to beat the algorithm and rise to the top. Get your copy today and become the next social media sensation! _ MR. BIG WEALTH is a 164-page book that unveils the secrets to beating the Facebook algorithm and becoming the number one superstar. Packed with invaluable insights, strategies, and tactics, this book is your ultimate guide to reaching new heights of success on the world's largest social media platform. Whether you're a business owner, influencer, or aspiring social media star, MR. BIG WEALTH equips you with the tools and knowledge to dominate Facebook and achieve unparalleled success. Unlock your potential and become the superstar you were meant to be with MR. BIG WEALTH.
The Balanced Algorithm Addressing Bias And Ethical Concerns In Ai
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Author : S Williams
language : en
Publisher: NFT Publishing
Release Date : 2025-04-13
The Balanced Algorithm Addressing Bias And Ethical Concerns In Ai written by S Williams and has been published by NFT Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-13 with Computers categories.
In an era where artificial intelligence (AI) shapes everything from hiring decisions to healthcare outcomes, ensuring fairness, transparency, and trust has never been more critical. The Balanced Algorithm delves deep into the pressing issues of algorithmic bias , discrimination in AI systems , and the growing demand for ethical AI practices . This groundbreaking book explores how biases emerge—from flawed training data and model design to entrenched societal inequalities—and offers actionable strategies to identify, mitigate, and prevent them. Through comprehensive analysis and real-world case studies, readers will uncover the science behind algorithmic bias , including cutting-edge statistical methods , fairness metrics , and innovative debiasing techniques . From industries like law enforcement, lending, and healthcare to sensitive domains requiring equitable access, this book examines both failures and successes in deploying responsible AI solutions . But addressing bias is only part of the equation. The Balanced Algorithm also tackles broader ethical concerns , such as privacy risks , public mistrust , and the societal implications of opaque algorithms. It provides a roadmap for overcoming barriers like algorithmic opacity , regulatory gaps, and accountability challenges while introducing emerging trends like explainable AI (XAI) , fairness-aware algorithms , and advanced bias detection platforms . Grounded in universal principles of justice and inclusivity, this book applies frameworks like Kantian ethics to guide developers, policymakers, and stakeholders toward creating human-centered AI systems that respect individual rights and foster long-term benefits for communities. With insights into existing legal considerations , proposed regulatory frameworks , and consumer protection measures , it equips readers with the tools needed to navigate complex debates on accountability, discrimination, and the future of trustworthy AI . Whether you're a technologist seeking to integrate fairness metrics into your workflows, a policymaker shaping guidelines for equitable algorithms , or simply someone passionate about the intersection of technology and society, The Balanced Algorithm is your essential guide to building a future where AI is not just powerful but also fair, transparent, and aligned with our shared values.
Syntactical Constructs And Algorithmic Paradigms In Python A Comprehensive Guide
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Author : BALACHANDAR RAMALINGAM RAKESH JENA IMRAN KHAN PROF. (DR) ARPIT JAIN
language : en
Publisher: DeepMisti Publication
Release Date : 2024-10-24
Syntactical Constructs And Algorithmic Paradigms In Python A Comprehensive Guide written by BALACHANDAR RAMALINGAM RAKESH JENA IMRAN KHAN PROF. (DR) ARPIT JAIN and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-24 with Business & Economics categories.
In the ever-evolving landscape of the modern world, the synergy between technology and management has become a cornerstone of innovation and progress. This book, Syntactical Constructs and Algorithmic Paradigms in Python: A Comprehensive Guide, is conceived to bridge the gap between emerging technological advancements in programming and their strategic application in the development of robust algorithms and software systems. Our objective is to equip readers with the tools and insights necessary to excel in this dynamic intersection of fields. This book is structured to provide a comprehensive exploration of the methodologies and strategies that define Python's innovation, particularly its syntactical constructs and algorithmic paradigms, and their integration into modern software development practices. From foundational theories to advanced applications, we delve into the critical aspects that drive successful programming in real-world environments. We have made a concerted effort to present complex concepts in a clear and accessible manner, making this work suitable for a diverse audience, including students, developers, and industry professionals. In authoring this book, we have drawn upon the latest research and best practices to ensure that readers not only gain a robust theoretical understanding but also acquire practical skills that can be applied in a variety of programming scenarios. The chapters are designed to strike a balance between depth and breadth, covering topics ranging from basic Python syntax and programming principles to advanced algorithm design and optimization. Additionally, we emphasize the importance of effective communication, dedicating sections to the art of presenting programming ideas and solutions in a precise and academically rigorous manner. The inspiration for this book arises from a recognition of the crucial role that Python and algorithmic design play in shaping the future of software development. We are profoundly grateful to Chancellor Shri Shiv Kumar Gupta of Maharaja Agrasen Himalayan Garhwal University for his unwavering support and vision. His dedication to fostering academic excellence and promoting a culture of innovation has been instrumental in bringing this project to fruition. We hope this book will serve as a valuable resource and inspiration for those eager to deepen their understanding of how Python programming and algorithmic paradigms can be harnessed together to drive innovation. We believe that the knowledge and insights contained within these pages will empower readers to lead the way in creating innovative solutions that will define the future of software development. Thank you for joining us on this journey. Authors
Mastering Machine Learning Algorithms Practical Applications Using Python And R
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Author : AKASH BALAJI MALI NAGARJUNA PUTTA GOKUL SUBRAMANIAN PROF. (DR) ARPIT JAIN
language : en
Publisher: DeepMisti Publication
Release Date : 2024-11-10
Mastering Machine Learning Algorithms Practical Applications Using Python And R written by AKASH BALAJI MALI NAGARJUNA PUTTA GOKUL SUBRAMANIAN PROF. (DR) ARPIT JAIN and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-10 with Computers categories.
In the ever-evolving landscape of the modern world, the synergy between technology and management has become a cornerstone of innovation and progress. This book, Mastering Machine Learning Algorithms: Practical Applications Using Python and R, is conceived to bridge the gap between emerging technological advancements in machine learning and their strategic application in various domains. Our objective is to equip readers with the tools and insights necessary to excel in this dynamic field. This book is structured to provide a comprehensive exploration of the methodologies and strategies that define the innovation of machine learning algorithms, particularly focusing on practical applications using Python and R. From foundational theories to advanced implementations, we delve into the critical aspects that drive successful application of machine learning techniques across industries. We have made a concerted effort to present complex concepts in a clear and accessible manner, making this work suitable for a diverse audience, including students, managers, and industry professionals. In authoring this book, we have drawn upon the latest research and best practices to ensure that readers not only gain a robust theoretical understanding but also acquire practical skills that can be applied in real-world scenarios. The chapters are designed to strike a balance between depth and breadth, covering topics ranging from algorithm development and data processing to strategic management of machine learning projects. Additionally, we emphasize the importance of effective communication, dedicating sections to the art of presenting innovative ideas and solutions in a precise and academically rigorous manner. The inspiration for this book arises from a recognition of the crucial role that machine learning algorithms and their practical applications play in shaping the future of industries. We are profoundly grateful to Chancellor Shri Shiv Kumar Gupta of Maharaja Agrasen Himalayan Garhwal University for his unwavering support and vision. His dedication to fostering academic excellence and promoting a culture of innovation has been instrumental in bringing this project to fruition. We hope this book will serve as a valuable resource and inspiration for those eager to deepen their understanding of how machine learning algorithms, applied through Python and R, can be harnessed to drive innovation. We believe that the knowledge and insights contained within these pages will empower readers to lead the way in creating innovative solutions that will define the future of data-driven industries. Thank you for joining us on this journey. Authors
The Data Science Design Manual
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Author : Steven S. Skiena
language : en
Publisher: Springer
Release Date : 2017-07-01
The Data Science Design Manual written by Steven S. Skiena and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-01 with Computers categories.
This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)
Parallel Processing Of Discrete Optimization Problems
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Author : Panos M. Pardalos
language : en
Publisher: American Mathematical Soc.
Release Date : 1995
Parallel Processing Of Discrete Optimization Problems written by Panos M. Pardalos and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.
This book contains papers presented at the Workshop on Parallel Processing of Discrete Optimization Problems held at DIMACS in April 1994. The contents cover a wide spectrum of the most recent algorithms and applications in parallel processing of discrete optimization and related problems. Topics include parallel branch and bound algorithms, scalability, load balancing, parallelism and irregular data structures and scheduling task graphs on parallel machines. Applications include parallel algorithms for solving satisfiability problems, location problems, linear programming, quadratic and linear assignment problems. This book would be suitable as a textbook in advanced courses on parallel algorithms and combinatorial optimization.