An Intuitive Exploration of Artificial Intelligence Theory and Applications of Deep Learning /
Dube, Simant.
An Intuitive Exploration of Artificial Intelligence Theory and Applications of Deep Learning / [electronic resource] : by Simant Dube. - 1st ed. 2021. - XXII, 352 p. 76 illus., 72 illus. in color. online resource.
Part I, Foundations -- AI Sculpture -- Make Me Learn -- Images and Sequences -- Why AI Works -- Learning to Sculpt -- Unleashing the Power of Generation -- The Road Most Rewarded -- The Classical World -- Part II, Applications -- To See is to Believe -- Read, Read, Read -- Lend Me Your Ear -- Create Your Shire and Rivendell -- Math to Code to Petaflops -- AI and Business -- Part III, Road Ahead -- Keep Marching on -- Benevolent AI for All -- Am I Looking at Myself? -- App. A, Solutions -- Further Reading -- Acronyms -- Glossary -- References -- Index.
This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future. An Intuitive Exploration of Artificial Intelligence offers insightful details on how AI works and solves problems in computer vision, natural language understanding, speech understanding, reinforcement learning and synthesis of new content. From the classic problem of recognizing cats and dogs, to building autonomous vehicles, to translating text into another language, to automatically converting speech into text and back to speech, to generating neural art, to playing games, and the author's own experience in building solutions in industry, this book is about explaining how exactly the myriad applications of AI flow out of its immense potential.
9783030686246
10.1007/978-3-030-68624-6 doi
Artificial intelligence.
Machine learning.
Multiagent systems.
Pattern recognition systems.
Artificial Intelligence.
Machine Learning.
Multiagent Systems.
Automated Pattern Recognition.
Q334-342 TA347.A78
006.3
An Intuitive Exploration of Artificial Intelligence Theory and Applications of Deep Learning / [electronic resource] : by Simant Dube. - 1st ed. 2021. - XXII, 352 p. 76 illus., 72 illus. in color. online resource.
Part I, Foundations -- AI Sculpture -- Make Me Learn -- Images and Sequences -- Why AI Works -- Learning to Sculpt -- Unleashing the Power of Generation -- The Road Most Rewarded -- The Classical World -- Part II, Applications -- To See is to Believe -- Read, Read, Read -- Lend Me Your Ear -- Create Your Shire and Rivendell -- Math to Code to Petaflops -- AI and Business -- Part III, Road Ahead -- Keep Marching on -- Benevolent AI for All -- Am I Looking at Myself? -- App. A, Solutions -- Further Reading -- Acronyms -- Glossary -- References -- Index.
This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future. An Intuitive Exploration of Artificial Intelligence offers insightful details on how AI works and solves problems in computer vision, natural language understanding, speech understanding, reinforcement learning and synthesis of new content. From the classic problem of recognizing cats and dogs, to building autonomous vehicles, to translating text into another language, to automatically converting speech into text and back to speech, to generating neural art, to playing games, and the author's own experience in building solutions in industry, this book is about explaining how exactly the myriad applications of AI flow out of its immense potential.
9783030686246
10.1007/978-3-030-68624-6 doi
Artificial intelligence.
Machine learning.
Multiagent systems.
Pattern recognition systems.
Artificial Intelligence.
Machine Learning.
Multiagent Systems.
Automated Pattern Recognition.
Q334-342 TA347.A78
006.3