You're reading from Hands-On Neural Networks with Keras

Product typeBook

Published inMar 2019

Reading LevelIntermediate

PublisherPackt

ISBN-139781789536089

Edition1st Edition

Languages

Python

Tools

Keras

Concepts

Neural Networks

Author (1)

Niloy Purkait

Summary

In this chapter, we learned about recurren6t neural networks and their aptness at processing sequential time-dependent data. The concepts that you have learned can now be applied to any time-series dataset that you may stumble upon. While this holds true for use cases such as stock market data and time-series in nature, it would be unreasonable to expect fantastic results from feeding your network real time price changes only. This is simply because the elements that affect the market price of stocks (such as investor perception, information networks, and available resources) are not nearly reflected to the level that would allow proper statistical modeling. The key is representing all relevant information in the most learnable manner possible for your network to successfully encode valuable representations therefrom.

While we did extensively explore the learning mechanisms...

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Hands-On Neural Networks with Keras

Published in: Mar 2019Publisher: PacktISBN-13: 9781789536089

Author (1)

Niloy Purkait

Niloy Purkait is a technology and strategy consultant by profession. He currently resides in the Netherlands, where he offers his consulting services to local and international companies alike. He specializes in integrated solutions involving artificial intelligence, and takes pride in navigating his clients through dynamic and disruptive business environments. He has a masters in Strategic Management from Tilburg University, and a full specialization in data science from Michigan University. He has advanced industry grade certifications from IBM, in subjects like signal processing, cloud computing, machine and deep learning. He is also perusing advanced academic degrees in several related fields, and is a self-proclaimed lifelong learner.
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Author (1)

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