Ai And Algorithms
DOWNLOAD
Download Ai And Algorithms PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Ai And Algorithms book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
The Basics Of Ai Algorithms
DOWNLOAD
Author : Julian Vexley
language : en
Publisher: Independently Published
Release Date : 2025-10-11
The Basics Of Ai Algorithms written by Julian Vexley and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-11 with Computers categories.
Artificial Intelligence is transforming the modern world - but beneath the headlines about robots, automation, and smart machines lies something much simpler: the algorithm. These sets of rules, calculations, and logical steps are the beating heart of every intelligent system. In The Basics of AI Algorithms, Julian Vexley breaks down this vast and technical subject into ten clear, accessible chapters designed for the curious reader. This book explores how machines learn, adapt, and evolve through data. It starts with the core question - what exactly is an algorithm? - and then guides you through the major branches of machine learning: supervised learning, unsupervised learning, and reinforcement learning. From there, it examines the models that make AI work, including neural networks that mimic the brain, decision trees that provide clarity and structure, and ensemble methods that show the power of collaboration between multiple algorithms. Each chapter reveals one of the essential pillars of artificial intelligence, explaining complex concepts in plain English without formulas or jargon. You'll learn how Support Vector Machines find the best dividing line between data points, how K-Nearest Neighbours classify information by proximity, and how Gradient Descent helps machines improve themselves step by step - the same process that powers modern deep learning. Throughout the book, Vexley combines insight, historical context, and practical examples to show how algorithms shape the world around us - from search engines and medical diagnostics to voice recognition and autonomous vehicles. The writing is clear, engaging, and ideal for readers who want to understand AI without getting lost in mathematics or code. More than a technical primer, The Basics of AI Algorithms is a story about how logic became intelligence. It explains how centuries-old ideas from mathematics and philosophy have evolved into digital systems capable of analysing vast amounts of information and making decisions that impact millions of lives. It also explores the human side of AI: how data quality, ethical responsibility, and human oversight remain vital in a world increasingly governed by automation. By the end of this book, readers will not only understand how AI algorithms work but also why they matter - and how they continue to redefine creativity, problem-solving, and the nature of intelligence itself. Whether you're a student, professional, or simply fascinated by the technologies shaping the future, The Basics of AI Algorithms offers a clear, comprehensive, and thought-provoking introduction to the logic behind the machine. Chapters include: 01. The Core Concept: What Is an Algorithm in AI? 02. Supervised Learning: Learning from Labelled Examples 03. Unsupervised Learning: Discovering Hidden Patterns 04. Reinforcement Learning: Learning Through Trial and Error 05. Neural Networks: Mimicking the Human Brain 06. Decision Trees: Transparent and Interpretable Logic 07. Support Vector Machines: Finding the Best Separating Line 08. K-Nearest Neighbours: Learning by Proximity 09. Ensemble Methods: The Power of Collaboration 10. Gradient Descent: The Path to Optimisation The Basics of AI Algorithms is your essential guide to understanding how machines think - and how their logic is shaping the world of tomorrow.
Dominant Algorithms To Evaluate Artificial Intelligence From The View Of Throughput Model
DOWNLOAD
Author : Waymond Rodgers
language : en
Publisher: Bentham Science Publishers
Release Date : 2022-07-20
Dominant Algorithms To Evaluate Artificial Intelligence From The View Of Throughput Model written by Waymond Rodgers and has been published by Bentham Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-20 with Computers categories.
This book describes the Throughput Model methodology that can enable individuals and organizations to better identify, understand, and use algorithms to solve daily problems. The Throughput Model is a progressive model intended to advance the artificial intelligence (AI) field since it represents symbol manipulation in six algorithmic pathways that are theorized to mimic the essential pillars of human cognition, namely, perception, information, judgment, and decision choice. The six AI algorithmic pathways are (1) Expedient Algorithmic Pathway, (2) Ruling Algorithmic Guide Pathway, (3) Analytical Algorithmic Pathway, (4) Revisionist Algorithmic Pathway, (5) Value Driven Algorithmic Pathway, and (6) Global Perspective Algorithmic Pathway. As AI is increasingly employed for applications where decisions require explanations, the Throughput Model offers business professionals the means to look under the hood of AI and comprehend how those decisions are attained by organizations. Key Features: - Covers general concepts of Artificial intelligence and machine learning - Explains the importance of dominant AI algorithms for business and AI research - Provides information about 6 unique algorithmic pathways in the Throughput Model - Provides information to create a roadmap towards building architectures that combine the strengths of the symbolic approaches for analyzing big data - Explains how to understand the functions of an AI algorithm to solve problems and make good decisions - informs managers who are interested in employing ethical and trustworthiness features in systems. Dominant Algorithms to Evaluate Artificial Intelligence: From the view of Throughput Model is an informative reference for all professionals and scholars who are working on AI projects to solve a range of business and technical problems.
What To Do When Machines Do Everything
DOWNLOAD
Author : Malcolm Frank
language : en
Publisher: John Wiley & Sons
Release Date : 2017-01-18
What To Do When Machines Do Everything written by Malcolm Frank and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-18 with Business & Economics categories.
“Refreshingly thought-provoking...” – The Financial Times The essential playbook for the future of your business What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans it raises profound questions on the future of work and how companies compete. Illustrated with real-world cases, data, and insight, the authors provide clear strategic guidance and actionable steps to help you and your organization move ahead in a world where exponentially developing new technologies are changing how value is created. Written by a team of business and technology expert practitioners—who also authored Code Halos: How the Digital Lives of People, Things, and Organizations are Changing the Rules of Business—this book provides a clear path to the future of your work. The first part of the book examines the once in a generation upheaval most every organization will soon face as systems of intelligence go mainstream. The authors argue that contrary to the doom and gloom that surrounds much of IT and business at the moment, we are in fact on the cusp of the biggest wave of opportunity creation since the Industrial Revolution. Next, the authors detail a clear-cut business model to help leaders take part in this coming boom; the AHEAD model outlines five strategic initiatives—Automate, Halos, Enhance, Abundance, and Discovery—that are central to competing in the next phase of global business by driving new levels of efficiency, customer intimacy and innovation. Business leaders today have two options: be swallowed up by the ongoing technological evolution, or ride the crest of the wave to new profits and better business. This book shows you how to avoid your own extinction event, and will help you; Understand the untold full extent of technology's impact on the way we work and live. Find out where we're headed, and how soon the future will arrive Leverage the new emerging paradigm into a sustainable business advantage Adopt a strategic model for winning in the new economy The digital world is already transforming how we work, live, and shop, how we are governed and entertained, and how we manage our money, health, security, and relationships. Don't let your business—or your career—get left behind. What To Do When Machines Do Everything is your strategic roadmap to a future full of possibility and success. Or peril.
A Guided Tour Of Artificial Intelligence Research
DOWNLOAD
Author : Pierre Marquis
language : en
Publisher: Springer Nature
Release Date : 2020-05-08
A Guided Tour Of Artificial Intelligence Research written by Pierre Marquis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-08 with Technology & Engineering categories.
The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). This third volume is dedicated to the interfaces of AI with various fields, with which strong links exist either at the methodological or at the applicative levels. The foreword of this volume reminds us that AI was born for a large part from cybernetics. Chapters are devoted to disciplines that are historically sisters of AI: natural language processing, pattern recognition and computer vision, and robotics. Also close and complementary to AI due to their direct links with information are databases, the semantic web, information retrieval and human-computer interaction. All these disciplines are privileged places for applications of AI methods. This is also the case for bioinformatics, biological modeling and computational neurosciences. The developments of AI have also led to a dialogue with theoretical computer science in particular regarding computability and complexity. Besides, AI research and findings have renewed philosophical and epistemological questions, while their cognitive validity raises questions to psychology. The volume also discusses some of the interactions between science and artistic creation in literature and in music. Lastly, an epilogue concludes the three volumes of this Guided Tour of AI Research by providing an overview of what has been achieved by AI, emphasizing AI as a science, and not just as an innovative technology, and trying to dispel some misunderstandings.
Mastering Algorithms For Ai
DOWNLOAD
Author : Hesham Mohamed Elsherif
language : en
Publisher:
Release Date : 2024-09-15
Mastering Algorithms For Ai written by Hesham Mohamed Elsherif and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-15 with Computers categories.
At the heart of AI lies the concept of an algorithm. An algorithm is essentially a step-by-step procedure or formula for solving a problem. In the context of AI, algorithms are used to process data, identify patterns, learn from that data, and make decisions based on the knowledge gained. AI algorithms differ from traditional algorithms in that they often involve learning and adaptation. Traditional algorithms are rule-based, meaning that the instructions are explicitly programmed and fixed. AI algorithms, particularly in machine learning, are designed to improve over time by learning from data. They can adjust their behavior based on new information, becoming more accurate and efficient as they process more data. In this book, we aim to demystify AI algorithms and provide you with both theoretical and practical insights into how these algorithms work. Starting from the basics of what an algorithm is, we move toward more complex algorithms and their applications in AI. The book is divided into manageable sections that introduce algorithms in a step-by-step manner, with code examples and projects to reinforce learning. You'll not only understand how algorithms are structured but also how to apply them in real-world AI systems. Whether you are new to AI or seeking to deepen your expertise, this book will equip you with the tools to build, optimize, and deploy AI algorithms that drive intelligent systems. Our goal is to empower you with the knowledge and skills to navigate the world of AI algorithms, from foundational principles to cutting-edge techniques. As artificial intelligence (AI) continues to evolve and become increasingly integrated into our daily lives, understanding the underlying algorithms that power AI systems is no longer just the domain of specialists. AI algorithms have become essential tools for professionals in diverse industries, from healthcare and finance to marketing and robotics. But why is it so important to learn AI algorithms specifically? The answer lies in the profound impact these algorithms have on the effectiveness, efficiency, and intelligence of AI systems. Learning AI algorithms is about understanding how machines can solve problems, make decisions, and adapt in ways that mimic - or even surpass - human capabilities. "Mastering Algorithms for AI: From Basics to Advanced Techniques" is designed as a comprehensive guide that takes you step-by-step through the world of AI algorithms, starting from foundational concepts and progressing to advanced techniques. Whether you're a beginner looking to enter the field of artificial intelligence or an experienced professional seeking to deepen your understanding, this book provides a clear, structured learning path. The following guidelines will help you make the most of this resource as you embark on your journey to mastering AI algorithms. Mastering Algorithms for AI: From Basics to Advanced Techniques is designed to be a versatile, comprehensive guide that accommodates learners from all backgrounds. Whether you're a novice or an experienced AI professional, you can use this book to build a solid understanding of AI algorithms, develop practical coding skills, and work on real-world projects that reinforce learning. With its modular structure, hands-on projects, and in-depth theoretical insights, this book serves as both a learning resource and a reference guide, ensuring that you walk away with a deep understanding of AI algorithms and the confidence to apply them in your work or research.
A Guided Tour Of Artificial Intelligence Research
DOWNLOAD
Author : Pierre Marquis
language : en
Publisher: Springer Nature
Release Date : 2020-05-08
A Guided Tour Of Artificial Intelligence Research written by Pierre Marquis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-08 with Computers categories.
The purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). This second volume presents the main families of algorithms developed or used in AI to learn, to infer, to decide. Generic approaches to problem solving are presented: ordered heuristic search, as well as metaheuristics are considered. Algorithms for processing logic-based representations of various types (first-order formulae, propositional formulae, logic programs, etc.) and graphical models of various types (standard constraint networks, valued ones, Bayes nets, Markov random fields, etc.) are presented. The volume also focuses on algorithms which have been developed to simulate specific ‘intelligent” processes such as planning, playing, learning, and extracting knowledge from data. Finally, an afterword draws a parallel between algorithmic problems in operation research and in AI.
Algorithms And Architectures Of Artificial Intelligence
DOWNLOAD
Author : Enn Tõugu
language : en
Publisher: IOS Press
Release Date : 2007
Algorithms And Architectures Of Artificial Intelligence written by Enn Tõugu and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.
This book gives an overview of methods developed in artificial intelligence for search, learning, problem solving and decision-making. It gives an overview of algorithms and architectures of artificial intelligence that have reached the degree of maturity when a method can be presented as an algorithm, or when a well-defined architecture is known, e.g. in neural nets and intelligent agents. It can be used as a handbook for a wide audience of application developers who are interested in using artificial intelligence methods in their software products. Parts of the text are rather independent, so that one can look into the index and go directly to a description of a method presented in the form of an abstract algorithm or an architectural solution. The book can be used also as a textbook for a course in applied artificial intelligence. Exercises on the subject are added at the end of each chapter. Neither programming skills nor specific knowledge in computer science are expected from the reader. However, some parts of the text will be fully understood by those who know the terminology of computing well.
Algorithms An Introduction To The Computer Science Artificial Intelligence Used To Solve Human Decisions Advance Technology Optimize Habits Learn Faster Your Improve Life
DOWNLOAD
Author : Trustgenics
language : en
Publisher: Thomas William
Release Date :
Algorithms An Introduction To The Computer Science Artificial Intelligence Used To Solve Human Decisions Advance Technology Optimize Habits Learn Faster Your Improve Life written by Trustgenics and has been published by Thomas William this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Discover How Algorithms Shape & Impact Our World Now you might look at this title and shy away, thinking that a book with "Algorithms" in its title must be just for techies and computer scientists. However this book is very accessible to those with no background in computer science. Decisions Oftentimes Have Optimal Solutions Today, many decisions that could be made by human beings from predicting earthquakes to interpreting languages can now be made by computer algorithms with advanced analytic capabilities. Everyday we make millions of decisions from selecting a life partner, to organizing your closet, to scheduling your life, to having a conversation. However, these decisions may be imperfect due to limited experience, implicit biases, or faulty probabilistic reasoning. Algorithms can better predict human behavior than trained psychologists and with much simpler criteria. Studies continue to show that the algorithms can do a better job than experts in a range of fields. Artificial intelligence is reshaping healthcare, science, engineering and life. The results will make our lives more productive, better organized, and essentially, much happier. Everywhere you look, artificial intelligence is beginning to permeate all types of industries and expectations are that it will continue to grow in the future. Imagine The Possibilities More Accurate Medical Diagnoses Better Military Strategies That Could Save Lives Detect Abnormal Genes In An Unborn Child Predict Changes In Weather and Earthquake Safer Self-Driving Cars That Have Learned Your Personal Preferences Analyze DNA Samples & Identify Potential Medical Risks Smart Homes That Will Anticipate Your Every Needs Predicting Where Cyber Hackers & Online Threats May Occur This is a must read for anyone interested in what our digital future looks like. Join The Future
Machine Learning And Ai In Finance
DOWNLOAD
Author : German Creamer
language : en
Publisher: Routledge
Release Date : 2021-04-05
Machine Learning And Ai In Finance written by German Creamer and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-05 with Business & Economics categories.
The significant amount of information available in any field requires a systematic and analytical approach to select the most critical information and anticipate major events. During the last decade, the world has witnessed a rapid expansion of applications of artificial intelligence (AI) and machine learning (ML) algorithms to an increasingly broad range of financial markets and problems. Machine learning and AI algorithms facilitate this process understanding, modelling and forecasting the behaviour of the most relevant financial variables. The main contribution of this book is the presentation of new theoretical and applied AI perspectives to find solutions to unsolved finance questions. This volume proposes an optimal model for the volatility smile, for modelling high-frequency liquidity demand and supply and for the simulation of market microstructure features. Other new AI developments explored in this book includes building a universal model for a large number of stocks, developing predictive models based on the average price of the crowd, forecasting the stock price using the attention mechanism in a neural network, clustering multivariate time series into different market states, proposing a multivariate distance nonlinear causality test and filtering out false investment strategies with an unsupervised learning algorithm. Machine Learning and AI in Finance explores the most recent advances in the application of innovative machine learning and artificial intelligence models to predict financial time series, to simulate the structure of the financial markets, to explore nonlinear causality models, to test investment strategies and to price financial options. The chapters in this book were originally published as a special issue of the Quantitative Finance journal.
In Ai We Trust
DOWNLOAD
Author : Helga Nowotny
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-19
In Ai We Trust written by Helga Nowotny and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-19 with Science categories.
One of the most persistent concerns about the future is whether it will be dominated by the predictive algorithms of AI – and, if so, what this will mean for our behaviour, for our institutions and for what it means to be human. AI changes our experience of time and the future and challenges our identities, yet we are blinded by its efficiency and fail to understand how it affects us. At the heart of our trust in AI lies a paradox: we leverage AI to increase our control over the future and uncertainty, while at the same time the performativity of AI, the power it has to make us act in the ways it predicts, reduces our agency over the future. This happens when we forget that that we humans have created the digital technologies to which we attribute agency. These developments also challenge the narrative of progress, which played such a central role in modernity and is based on the hubris of total control. We are now moving into an era where this control is limited as AI monitors our actions, posing the threat of surveillance, but also offering the opportunity to reappropriate control and transform it into care. As we try to adjust to a world in which algorithms, robots and avatars play an ever-increasing role, we need to understand better the limitations of AI and how their predictions affect our agency, while at the same time having the courage to embrace the uncertainty of the future.