Design and create neural networks with deep learning and artificial
intelligence principles using OpenAI Gym, TensorFlow, and Keras Key
Features Explore neural network architecture and understand how it
functions Learn algorithms to solve common problems using back
propagation and perceptrons Understand how to apply neural networks
to applications with the help of useful illustrations Book
DescriptionNeural networks play a very important role in deep
learning and artificial intelligence (AI), with applications in a
wide variety of domains, right from medical diagnosis, to financial
forecasting, and even machine diagnostics. Hands-On Neural Networks
is designed to guide you through learning about neural networks in
a practical way. The book will get you started by giving you a
brief introduction to perceptron networks. You will then gain
insights into machine learning and also understand what the future
of AI could look like. Next, you will study how embeddings can be
used to process textual data and the role of long short-term memory
networks (LSTMs) in helping you solve common natural language
processing (NLP) problems. The later chapters will demonstrate how
you can implement advanced concepts including transfer learning,
generative adversarial networks (GANs), autoencoders, and
reinforcement learning. Finally, you can look forward to further
content on the latest advancements in the field of neural networks.
By the end of this book, you will have the skills you need to
build, train, and optimize your own neural network model that can
be used to provide predictable solutions. What you will learn Learn
how to train a network by using backpropagation Discover how to
load and transform images for use in neural networks Study how
neural networks can be applied to a varied set of applications
Solve common challenges faced in neural network development
Understand the transfer learning concept to solve tasks using Keras
and Visual Geometry Group (VGG) network Get up to speed with
advanced and complex deep learning concepts like LSTMs and NLP
Explore innovative algorithms like GANs and deep reinforcement
learning Who this book is forIf you are interested in artificial
intelligence and deep learning and want to further your skills,
then this intermediate-level book is for you. Some knowledge of
statistics will help you get the most out of this book.
General
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