LEADER 03872nam  2200373I  450 
001 9910548221403321
005 20220811143749.0
010   $a9781788990028
035   $a(EXLCZ)994920000000457463
100   $a20200805d2018      uy             0
101 0 $aeng
200 10$aArtificial intelligence by example$b[electronic resource] : develop machine intelligence from scratch using real artificial intelligence use cases /$fDenis Rothman
205   $aSecond edition.
210  1$aBirmingham, UK :$cPackt Publishing,$d2018.
215   $a1 online resource (1 volume) $cillustrations
320   $aIncludes bibliographical references and index.
330   $aUnderstand the fundamentals and develop your own AI solutions in this updated edition packed with many new examples Key Features AI-based examples to guide you in designing and implementing machine intelligence Build machine intelligence from scratch using artificial intelligence examples Develop machine intelligence from scratch using real artificial intelligence Book Description AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions. What you will learn Apply k-nearest neighbors (KNN) to language translations and explore the opportunities in Google Translate Understand chained algorithms combining unsupervised learning with decision trees Solve the XOR problem with feedforward neural networks (FNN) and build its architecture to represent a data flow graph Learn about meta learning models with hybrid neural networks Create a chatbot and optimize its emotional intelligence deficiencies with tools such as Small Talk and data logging Building conversational user interfaces (CUI) for chatbots Writing genetic algorithms that optimize deep learning neural networks Build quantum computing circuits Who this book is for Developers and those interested in AI, who want to understand the fundamentals of Artificial Intelligen...
606   $aArtificial intelligence$xData processing
606   $aApplication software$xDevelopment
606   $aMachine learning
606   $aNeural networks (Computer science)
606   $aPython (Computer program language)
606   $aCloud computing
608   $aElectronic books.
615  0$aArtificial intelligence$xData processing.
615  0$aApplication software$xDevelopment.
615  0$aMachine learning.
615  0$aNeural networks (Computer science)
615  0$aPython (Computer program language)
615  0$aCloud computing.
700   $aRothman$b Denis$01183299
912   $a9910548221403321
996   $aArtificial Intelligence By Example$92744914
997   $aUNINA