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What you would learn in Recurrent Neural Networks course?
Start with the recurrent neural networks (RNN) principles in a way that is easy to understand and develop simple applications using RNNs and Keras. RNN is one of the fastest-growing areas in the AI world. The most well-known and innovative applications, such as speech synthesis, translation of languages, question answering, and text generation, use RNNs as their foundation technology. Learning about this technology, however, faces many issues. Many learning materials have a heavy math component and are challenging to navigate without math knowledge. IT professionals of different backgrounds require a more straightforward tool to grasp the fundamentals and quickly build models. This course by Kumaran Ponnambalam provides a simplified guide to learning the fundamentals of recurrent networks, which will allow users to be productive in a short time. Kumaran begins with a simple introduction to RNN before guiding you through the process of creating models. Then, he explains the common elements of RNN, including LSTMs, GRUs Word embeddings, and transformers.
1. Introduction to RNNs
2. RNN Concepts
3. An RNN Example
4. RNN Architectures
5. An LSTM Example
6. Word Embeddings
7. Spam Detection with Word Embeddings
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