Free Download Hands-On Artificial Intelligence for Beginners: An introduction to AI concepts, algorithms, and their implementation by Patrick D. Smith
English | October 31, 2019 | ISBN: 1788991060 | 362 pages | MOBI | 8.57 Mb
Grasp the fundamentals of Artificial Intelligence and build your own intelligent systems with ease
Key FeaturesEnter the world of AI with the help of solid concepts and real-world use casesExplore AI components to build real-world automated intelligenceBecome well versed with machine learning and deep learning concepts
Book Description
Virtual Assistants, such as Alexa and Siri, process our requests, Google's cars have started to read addresses, and Amazon's prices and Netflix's recommended videos are decided by AI. Artificial Intelligence is one of the most exciting technologies and is becoming increasingly significant in the modern world.
Hands-On Artificial Intelligence for Beginners will teach you what Artificial Intelligence is and how to design and build intelligent applications. This book will teach you to harness packages such as TensorFlow in order to create powerful AI systems. You will begin with reviewing the recent changes in AI and learning how artificial neural networks (ANNs) have enabled more intelligent AI. You'll explore feedforward, recurrent, convolutional, and generative neural networks (FFNNs, RNNs, CNNs, and GNNs), as well as reinforcement learning methods. In the concluding chapters, you'll learn how to implement these methods for a variety of tasks, such as generating text for chatbots, and playing board and video games.
By the end of this book, you will be able to understand exactly what you need to consider when optimizing ANNs and how to deploy and maintain AI applications.
What you will learnUse TensorFlow packages to create AI systemsBuild feedforward, convolutional, and recurrent neural networksImplement generative models for text generationBuild reinforcement learning algorithms to play gamesAssemble RNNs, CNNs, and decoders to create an intelligent assistantUtilize RNNs to predict stock market behaviorCreate and scale training pipelines and deployment architectures for AI systems
Who this book is for
This book is designed for beginners in AI, aspiring AI developers, as well as machine learning enthusiasts with an interest in leveraging various algorithms to build powerful AI applications.
Table of ContentsThe History of AIMachine Learning BasicsPlatforms and Other EssentialsYour First Artificial Neural NetworksConvolutional Neural NetworksRecurrent Neural NetworksGenerative ModelsReinforcement LearningDeep Learning for Intelligent AgentsDeep Learning for Game PlayingDeep Learning for FinanceDeep Learning for RoboticsDeploying and Maintaining AI Applications
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