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Hands-On Artificial Intelligence for Beginners

Hands-On Artificial Intelligence for Beginners

By : Dindi, Patrick D. Smith
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Hands-On Artificial Intelligence for Beginners

Hands-On Artificial Intelligence for Beginners

By: Dindi, Patrick D. Smith

Overview of this book

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.
Table of Contents (15 chapters)
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Other forms of generative models

While we've only covered two types of generative model, there are many different types that you may encounter in the literature. The following chart is not exhaustive, but does provide a general overview of the types of generative models out there:

Let's break this down:

  • Explicit density models: Model our data directly from a probability distribution. We explicitly define the probability and solve for it
  • Implicit density models: Learn to sample from a probability distribution without defining what that distribution is

Within explicit density models, we have tractable density models and approximate density models. Here, tractable is related to defined computational time; we can calculate the computational complexity of a tractable problem. Approximate density relates to intractability—a computer science term that means that...

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