Understanding RNNs

Recurrent Neural Networks(RNNs) are a type of Artificial Neural Networks(ANNs) which introduces us to the realm of Deep Learning, an aspect that has been significantly contributing to the evolution of Data Analysis. RNNs are specifically designed to recognize patterns in sequences of data, such as text, genomes, handwriting, or the spoken word. This inherent feature of RNNs makes them extremely useful and versatile for a data analyst.

A data analyst leveraging RNNs can effectively charter the intrinsic complexity of data sequences, classify them, and make accurate predictions. With the fundamental understanding of deep learning, data analysts can unlock the full potential of RNNs in delivering insightful data analysis that goes beyond traditional statistical methods. Modern research and applications of RNNs extend to multiple domains including natural language processing, speech recognition, and even in the financial sphere for stock price prediction making this a key tool in a data analyst’s arsenal.

Visit the following resources to learn more:

• @article@What is a Recurrent Neural Network (RNN)?
• @article@Recurrent Neural Networks Cheat-sheet