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Why machines learn : the elegant math behind modern AI / by Ananthaswamy, Anil,author.(CARDINAL)389919;
Includes bibliographical references (pages [435]-453) and index.Desperately seeking patterns -- We are all just numbers here... -- The bottom of the bowl -- In all probability -- Birds of a feather -- There's magic in them matrices -- The great kernel rope trick -- With a little help from physics -- The man who set back deep learning (not really) -- The algorithm that put paid to a persistent myth -- The eyes of a machine -- Terra incognita."A rich, narrative explanation of the mathematics that has brought us machine learning and the ongoing explosion of artificial intelligence"--
Subjects: Machine learning.; Deep learning (Machine learning); Artificial intelligence.; Mathematics.;
Available copies: 2 / Total copies: 2
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From deep learning to rational machines : what the history of philosophy can teach us about the future of artifical intelligence / by Buckner, Cameron J.,author.(CARDINAL)894786;
Includes bibliographic references (pages 349-401) and index."This book provides a framework for thinking about foundational philosophical questions surrounding the use of deep artificial neural networks ("deep learning") to achieve artificial intelligence. Specifically, it link recent breakthroughs to classic works in empiricist philosophy of mind. In recent assessments of deep learning's potential, scientists have cited historical figures from the philosophical debate between nativism and empiricism, which concerns the origins of abstract knowledge. These emiricists were faculty psychologists; that is, they argued that the extraction of abstract knowledge from experience involves the active engagement of psychological faculties such as perception, memory, imagination, attention, and empathy. This book explains how recent deep learning breakthroughs realized some of the most ambitious ideas about these faculties from philosophers such as Aristotle, Ibn Sina (Avicenna), John Locke, David Hume, William James, and Sophie de Grouchy. It illustrates the utility of this interdisciplinary connection by showing how it can provide benefits to both philosophy and computer science: computer scientists can continue to mine the history of philosophy for ideas and aspirational targets to hit, and philosophers can see how some of the historical empricists' most ambitious speculations can now be realized in specific computational systems"--Includes bibliographical references and index.Moderate empiricism and machine learning -- What is deep learning, and how should we evaluate its potential? -- Perception -- Memory -- Imagination -- Attention -- Social and moral cognition.
Subjects: Machine learning; Artificial intelligence;
Available copies: 1 / Total copies: 1
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Deep learning with Python / by Chollet, François,author.(CARDINAL)785614;
Includes bibliographical references and index.Part 1: Fundamentals of deep learning. What is deep learning? -- Before we begin: the mathematical building blocks of neural networks -- Getting started with neural networks -- Fundamentals of machine learning -- Part 2: Deep learning in practice. Deep learning for computer vision -- Deep learning for text and sequences -- Advanced deep-learning best practices -- Generative deep learning.Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. --
Subjects: Python (Computer program language); Machine learning.; Neural networks (Computer science);
Available copies: 1 / Total copies: 1
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Applied machine learning and AI for engineers : solve business problems that can't be solved algorithmically / by Prosise, Jeffauthor.(CARDINAL)879138; Prosise, Adam,writer of foreword.;
Includes bibliographical references and index.Part 1. Machine learning with Schikit-learn. Machine learning -- Regression models -- Classification models -- Text classification -- Support vector machines -- Principal component analysis -- Operationalizing machine learning models -- Part 2. Deep learning with Keras and TensorFlow. Deep learning -- Neural networks -- Image classification with convolutional neural networks -- Face detection and recognition -- Object detection -- Natural language processing -- Azure cognitive services.While many introductory guides to AI are calculus books in disguise, this one mostly eschews the math. Instead, author Jeff Prosise helps engineers and software developers build an intuitive understanding of AI to solve business problems. Need to create a system to detect the sounds of illegal logging in the rainforest, analyze text for sentiment, or predict early failures in rotating machinery? This practical book teaches you the skills necessary to put AI and machine learning to work at your company.
Subjects: Artificial intelligence.; Machine learning.;
Available copies: 1 / Total copies: 1
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AI basics / by Olson, Elsie,1986-author.(CARDINAL)415116;
Includes bibliographical references and index.Man vs. machine -- A history of AI -- AI today -- The future of AI -- Glossary."Dive deep into artificial intelligence, from what it is to how it works. Readers discover the history of machine learning. They also learn how AI is used currently and explore the technology's future"--Ages 8-12Grades 4-6
Subjects: Artificial intelligence; Artificial intelligence;
Available copies: 0 / Total copies: 1
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Artificial intelligence programming with Python : from zero to hero / by Xiao, Perry,author.;
Part I--Introduction -- Chapter 1: Introduction to AI -- Chapter 2: AI Development Tools -- Part II--Machine Learning and Deep Learning -- Chapter 3: Machine Learning -- Chapter 4: Deep Learning -- Part III--AI Applications -- Chapter 5: Image Classification -- Chapter 6: Face Detection and Face Recognition -- Chapter 7: Object Detections and Image Segmentations -- Chapter 8: Pose Detection -- Chapter 9: GAN and Neural-Style Transfer -- Chapter 10: Natural Language Processing -- Chapter 11: Data Analysis -- Chapter 12: Advanced AI Computing.A hands-on roadmap to using Python for artificial intelligence programming In Practical Artificial Intelligence Programming with Python: From Zero to Hero, veteran educator and photophysicist Dr. Perry Xiao delivers a thorough introduction to one of the most exciting areas of computer science in modern history. The book demystifies artificial intelligence and teaches readers its fundamentals from scratch in simple and plain language and with illustrative code examples. Divided into three parts, the author explains artificial intelligence generally, machine learning, and deep learning. It tackles a wide variety of useful topics, from classification and regression in machine learning to generative adversarial networks. He also includes: Fulsome introductions to MATLAB, Python, AI, machine learning, and deep learning Expansive discussions on supervised and unsupervised machine learning, as well as semi-supervised learning Practical AI and Python "cheat sheet" quick references This hands-on AI programming guide is perfect for anyone with a basic knowledge of programming--including familiarity with variables, arrays, loops, if-else statements, and file input and output--who seeks to understand foundational concepts in AI and AI development.
Subjects: Python (Computer program language); Artificial intelligence.;
Available copies: 1 / Total copies: 1
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Becoming a data head : how to think, speak, and understand data science, statistics, and machine learning / by Gutman, Alex J.,author.; Goldmeier, Jordan,author.;
PART ONE: Thinking like a data head. What is the problem? ; What is data? ; Prepare to think statistically -- PART TWO: Speaking like a data head: Argue with the data ; Explore the data ; Examine the probabilities ; Challange the statistics -- PART THREE: Understanding the data scientist's toolbox. Search for hidden groups ; Understand the regression model ; Understand the classification model ; Understand the text analytics ; Conceptualize deep learning -- PART FOUR: Ensuring success. Watch out for pitfalls ; Know the people and personalities ; What's next?Includes bibliographical references and index.
Subjects: Handbooks and manuals.; Data mining.; Machine learning.;
Available copies: 1 / Total copies: 1
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Python programming for beginners : 2 books in 1 / by Reed, Mark.(CARDINAL)860572;
Includes bibliographic references."Python is a great programming language. It is also the simplest to learn. It has gained popularity in a number of technological domains, including Machine Learning, Deep Learning, and Data Science. With Python's increasing popularity in many technical domains, now is the greatest moment to learn the language. Python programming - 2 books in 1 aims to make it simple for you to begin your journey, regardless of your skills or expertise. Each chapter of this book builds on the previous chapters in an easy step-by-step approach"--
Subjects: Computer programming.; Python (Computer program language);
Available copies: 0 / Total copies: 1
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Machines.
Enter a world of monster excavators, Mach 9.6 jets, deep-space probes, microscopic nanobots and more marvelous machines, and learn how they've impacted our world.
Subjects: Machinery;
Available copies: 3 / Total copies: 3
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Computational formalism : art history and machine learning / by Wasielewski, Amanda,author.(CARDINAL)873762; MIT Press,publisher.;
Includes bibliographical references and index."Computational Formalism investigates examples of art historical analysis in the fields of computer and information sciences, and frames this research in the context of art historiography. The use of machine learning to analyze art images has ushered in a renewed interest in formalism in art history, but these new techniques create new critical challenges for the field"--
Subjects: Art; Art;
Available copies: 1 / Total copies: 1
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Results 1 to 10 of 84 |