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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Artificial Intelligence By Example - Acquire advanced AI, machine learning, and deep learning design skills, 2nd Edition (Paperback, 2nd Revised edition)
Loot Price: R1,285
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Artificial Intelligence By Example - Acquire advanced AI, machine learning, and deep learning design skills, 2nd Edition (Paperback, 2nd Revised edition)
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Understand 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 DescriptionAI 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 forDevelopers and
those interested in AI, who want to understand the fundamentals of
Artificial Intelligence and implement them practically. Prior
experience with Python programming and statistical knowledge is
essential to make the most out of this book.
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