Author: Boston (Mass.). School CommitteePublisher:
ISBN:
Category :
Languages : en
Pages : 1120
Book Description
Documents
Author: Boston (Mass.). School CommitteePublisher:
ISBN:
Category :
Languages : en
Pages : 1120
Book Description
School Document
Author: Suggested Books for Indian Schools
Author: United States. Bureau of Indian AffairsPublisher:
ISBN:
Category : Children's literature
Languages : en
Pages : 170
Book Description
Educational Bulletin
Author: Report of the State School Book Commission, 1923
Author: Ohio. State School Book CommissionPublisher:
ISBN:
Category : Textbooks
Languages : en
Pages : 262
Book Description
The Publishers Weekly
Author: Publisher:
ISBN:
Category : American literature
Languages : en
Pages : 1238
Book Description
The American Educational Catalogue
Author: Educational Bulletin
Author: Kentucky. Dept. of EducationPublisher:
ISBN:
Category :
Languages : en
Pages : 526
Book Description
The Journal of Educational Research
Author: Essential Math for AI
Author: Hala NelsonPublisher: "O'Reilly Media, Inc."
ISBN: 1098107586
Category : Computers
Languages : en
Pages : 1128
Book Description
Companies are scrambling to integrate AI into their systems and operations. But to build truly successful solutions, you need a firm grasp of the underlying mathematics. This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory. Engineers, data scientists, and students alike will examine mathematical topics critical for AI--including regression, neural networks, optimization, backpropagation, convolution, Markov chains, and more--through popular applications such as computer vision, natural language processing, and automated systems. And supplementary Jupyter notebooks shed light on examples with Python code and visualizations. Whether you're just beginning your career or have years of experience, this book gives you the foundation necessary to dive deeper in the field. Understand the underlying mathematics powering AI systems, including generative adversarial networks, random graphs, large random matrices, mathematical logic, optimal control, and more Learn how to adapt mathematical methods to different applications from completely different fields Gain the mathematical fluency to interpret and explain how AI systems arrive at their decisions