Algorithms of Intelligence: Exploring the World of Machine Learning

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Author :
Publisher : Inkbound Publishers
ISBN 13 : 8196822340
Total Pages : 224 pages
Book Rating : 4.47/5 ( download)

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Book Synopsis Algorithms of Intelligence: Exploring the World of Machine Learning by : Dr R. Keerthika

Download or read book Algorithms of Intelligence: Exploring the World of Machine Learning written by Dr R. Keerthika and published by Inkbound Publishers. This book was released on 2022-01-20 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Delve into the fascinating world of machine learning with this comprehensive guide, which unpacks the algorithms driving today's intelligent systems. From foundational concepts to advanced applications, this book is essential for anyone looking to understand the mechanics behind AI.

Genetic Algorithms and Machine Learning for Programmers

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Publisher : Pragmatic Bookshelf
ISBN 13 : 1680506587
Total Pages : 307 pages
Book Rating : 4.87/5 ( download)

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Book Synopsis Genetic Algorithms and Machine Learning for Programmers by : Frances Buontempo

Download or read book Genetic Algorithms and Machine Learning for Programmers written by Frances Buontempo and published by Pragmatic Bookshelf. This book was released on 2019-01-23 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you. Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems. In this book, you will: Use heuristics and design fitness functions. Build genetic algorithms. Make nature-inspired swarms with ants, bees and particles. Create Monte Carlo simulations. Investigate cellular automata. Find minima and maxima, using hill climbing and simulated annealing. Try selection methods, including tournament and roulette wheels. Learn about heuristics, fitness functions, metrics, and clusters. Test your code and get inspired to try new problems. Work through scenarios to code your way out of a paper bag; an important skill for any competent programmer. See how the algorithms explore and learn by creating visualizations of each problem. Get inspired to design your own machine learning projects and become familiar with the jargon. What You Need: Code in C++ (>= C++11), Python (2.x or 3.x) and JavaScript (using the HTML5 canvas). Also uses matplotlib and some open source libraries, including SFML, Catch and Cosmic-Ray. These plotting and testing libraries are not required but their use will give you a fuller experience. Armed with just a text editor and compiler/interpreter for your language of choice you can still code along from the general algorithm descriptions.

A Human's Guide to Machine Intelligence

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Author :
Publisher : Penguin
ISBN 13 : 0525560904
Total Pages : 274 pages
Book Rating : 4.06/5 ( download)

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Book Synopsis A Human's Guide to Machine Intelligence by : Kartik Hosanagar

Download or read book A Human's Guide to Machine Intelligence written by Kartik Hosanagar and published by Penguin. This book was released on 2020-03-10 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me. Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.

Machine Learning and AI in Finance

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Author :
Publisher : Routledge
ISBN 13 : 1000372049
Total Pages : 206 pages
Book Rating : 4.45/5 ( download)

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Book Synopsis Machine Learning and AI in Finance by : German Creamer

Download or read book Machine Learning and AI in Finance written by German Creamer and published by Routledge. This book was released on 2021-04-06 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Practical Deep Learning for Cloud, Mobile, and Edge

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492034819
Total Pages : 585 pages
Book Rating : 4.10/5 ( download)

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Book Synopsis Practical Deep Learning for Cloud, Mobile, and Edge by : Anirudh Koul

Download or read book Practical Deep Learning for Cloud, Mobile, and Edge written by Anirudh Koul and published by "O'Reilly Media, Inc.". This book was released on 2019-10-14 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users

Artificial Intelligence (AI) Unleashed

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Author :
Publisher : Michael McNaught
ISBN 13 :
Total Pages : 51 pages
Book Rating : 4./5 ( download)

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Book Synopsis Artificial Intelligence (AI) Unleashed by : Michael McNaught

Download or read book Artificial Intelligence (AI) Unleashed written by Michael McNaught and published by Michael McNaught. This book was released on 2023-06-10 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step into a world where machines think, learn, and reshape our very existence. "Artificial Intelligence (AI) Unleashed: Exploring The Boundless Potential Of AI" is a captivating exploration of the transformative power of AI. From healthcare to finance, transportation to education, this book unravels the mysteries of AI, demystifying complex algorithms and showcasing real-world applications. Discover how AI is revolutionizing industries, empowering communities, and challenging our understanding of intelligence. Delve into the ethical considerations and responsible development of AI as we navigate the uncharted territories of bias, transparency, and accountability. With well researched information, this book is your guide to understanding and embracing the boundless potential of artificial intelligence. Get ready to embark on a journey that will reshape your perception of what is possible in the age of AI.

Rise of the Machines

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Author :
Publisher : IT Collection
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.12/5 ( download)

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Book Synopsis Rise of the Machines by : Christopher Ford

Download or read book Rise of the Machines written by Christopher Ford and published by IT Collection. This book was released on 2023-07-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, we explore the fascinating world of artificial intelligence, from its inception to its present-day applications and potential future implications. By examining the fundamental concepts, algorithms, and techniques, we aim to demystify AI and provide readers with a comprehensive understanding of this rapidly evolving field. We also delve into the ethical and societal considerations surrounding AI, ensuring that readers grasp both the promises and challenges associated with its implementation. Whether you are a novice curious about AI or a seasoned professional seeking deeper insights, this book will serve as a valuable resource, shedding light on the rise of machines and their impact on our world. Chapters included: Chapter 1: Introduction to Artificial Intelligence Chapter 2: The Fundamentals of AI Chapter 3: Machine Learning Algorithms Chapter 4: Deep Learning Chapter 5: Natural Language Processing Chapter 6: Robotics and AI Chapter 7: AI and Society Chapter 8: Future of AI Chapter 9: Ethical and Legal Implications Chapter 10: AI and Human Collaboration Chapter 11: The Philosophy of AI Chapter 12: Conclusion

Intelligent System Algorithms and Applications in Science and Technology

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Author :
Publisher : CRC Press
ISBN 13 : 1000406822
Total Pages : 428 pages
Book Rating : 4.25/5 ( download)

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Book Synopsis Intelligent System Algorithms and Applications in Science and Technology by : Sunil Pathak

Download or read book Intelligent System Algorithms and Applications in Science and Technology written by Sunil Pathak and published by CRC Press. This book was released on 2022-02-03 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 21st century has witnessed massive changes around the world in intelligence systems in order to become smarter, energy efficient, reliable, and cheaper. This volume explores the application of intelligent techniques in various fields of engineering and technology. It addresses diverse topics in such areas as machine learning-based intelligent systems for healthcare, applications of artificial intelligence and the Internet of Things, intelligent data analytics techniques, intelligent network systems and applications, and inequalities and process control systems. The authors explore the full breadth of the field, which encompasses data analysis, image processing, speech processing and recognition, medical science and healthcare monitoring, smart irrigation systems, insurance and banking, robotics and process control, and more.

Artificial Intelligence in Practice

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Publisher : John Wiley & Sons
ISBN 13 : 1119548217
Total Pages : 351 pages
Book Rating : 4.18/5 ( download)

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Book Synopsis Artificial Intelligence in Practice by : Bernard Marr

Download or read book Artificial Intelligence in Practice written by Bernard Marr and published by John Wiley & Sons. This book was released on 2019-05-28 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.

Introducing Machine Learning

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Author :
Publisher : Microsoft Press
ISBN 13 : 0135588383
Total Pages : 616 pages
Book Rating : 4.83/5 ( download)

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Book Synopsis Introducing Machine Learning by : Dino Esposito

Download or read book Introducing Machine Learning written by Dino Esposito and published by Microsoft Press. This book was released on 2020-01-31 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master machine learning concepts and develop real-world solutions Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft’s powerful ML.NET library, including capabilities for data processing, training, and evaluation. They present families of algorithms that can be trained to solve real-life problems, as well as deep learning techniques utilizing neural networks. The authors conclude by introducing valuable runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning. · 14-time Microsoft MVP Dino Esposito and Francesco Esposito help you · Explore what’s known about how humans learn and how intelligent software is built · Discover which problems machine learning can address · Understand the machine learning pipeline: the steps leading to a deliverable model · Use AutoML to automatically select the best pipeline for any problem and dataset · Master ML.NET, implement its pipeline, and apply its tasks and algorithms · Explore the mathematical foundations of machine learning · Make predictions, improve decision-making, and apply probabilistic methods · Group data via classification and clustering · Learn the fundamentals of deep learning, including neural network design · Leverage AI cloud services to build better real-world solutions faster About This Book · For professionals who want to build machine learning applications: both developers who need data science skills and data scientists who need relevant programming skills · Includes examples of machine learning coding scenarios built using the ML.NET library