Price: $54.99
(as of Dec 24,2024 08:42:53 UTC – Details)
Publisher : Springer; 2000th edition (May 30, 2000)
Language : English
Paperback : 149 pages
ISBN-10 : 185233343X
ISBN-13 : 978-1852333430
Item Weight : 8.8 ounces
Dimensions : 6.1 x 0.37 x 9.17 inches
In this post, we will delve into the fascinating world of Recurrent Neural Networks (RNNs) and explore how they can be used for learning complex sequences of data. Specifically, we will be referencing the book “Learning with Recurrent Neural Networks (Lecture Notes in Control and Information Sciences, 254)” by Stefan Wermter and James Austin.
RNNs are a type of artificial neural network that is designed to handle sequential data, making them particularly well-suited for tasks such as speech recognition, language modeling, and time series prediction. Unlike traditional feedforward neural networks, RNNs have connections that loop back on themselves, allowing them to maintain a memory of previous inputs.
The book covers a wide range of topics related to RNNs, including their architecture, training algorithms, and applications in various fields. It also delves into more advanced topics such as long short-term memory (LSTM) networks and gated recurrent units (GRUs), which have been developed to address the issue of vanishing gradients in traditional RNNs.
By studying the contents of this book, readers can gain a deeper understanding of how RNNs work and how they can be applied to real-world problems. Whether you are a seasoned machine learning practitioner or a newcomer to the field, “Learning with Recurrent Neural Networks” is sure to provide valuable insights that will enhance your knowledge and skills in this exciting area of research.
So, if you are interested in learning more about RNNs and how they can be used to tackle challenging problems, be sure to check out this informative book. Happy reading and happy learning!
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