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You're reading from  Modern Time Series Forecasting with Python

Product typeBook
Published inNov 2022
PublisherPackt
ISBN-139781803246802
Edition1st Edition
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Manu Joseph
Manu Joseph
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Manu Joseph

Manu Joseph is a self-made data scientist with more than a decade of experience working with many Fortune 500 companies enabling digital and AI transformations, specifically in machine learning-based demand forecasting. He is considered an expert, thought leader, and strong voice in the world of time series forecasting. Currently, Manu leads applied research at Thoucentric, where he advances research by bringing cutting-edge AI technologies to the industry. He is also an active open-source contributor and developed an open-source library—PyTorch Tabular—which makes deep learning for tabular data easy and accessible. Originally from Thiruvananthapuram, India, Manu currently resides in Bengaluru, India, with his wife and son
Read more about Manu Joseph

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Temporal Fusion Transformer (TFT)

TFT is a model that is thoughtfully designed from the ground up to make the most efficient use of all the different kinds of information in a global modeling context – static and dynamic variables. TFT also has interpretability at the heart of all design decisions. The result is a high-performing, interpretable, and global DL model.

Reference check

The research paper by Lim et al. on TFT is cited in the References section as 10.

At first glance, the model architecture looks complicated and daunting. But once you peel the onion, it is quite simple and ingenious. We will take this one level of abstraction at a time to ease you into the full model. Along the way, there will be many black boxes I’m going to ask you to take for granted, but don’t worry – we will open every one of them as we dive deeper.

The Architecture of TFT

Let’s establish some notations and a setting before we start. We have a dataset...

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Modern Time Series Forecasting with Python
Published in: Nov 2022Publisher: PacktISBN-13: 9781803246802

Author (1)

author image
Manu Joseph

Manu Joseph is a self-made data scientist with more than a decade of experience working with many Fortune 500 companies enabling digital and AI transformations, specifically in machine learning-based demand forecasting. He is considered an expert, thought leader, and strong voice in the world of time series forecasting. Currently, Manu leads applied research at Thoucentric, where he advances research by bringing cutting-edge AI technologies to the industry. He is also an active open-source contributor and developed an open-source library—PyTorch Tabular—which makes deep learning for tabular data easy and accessible. Originally from Thiruvananthapuram, India, Manu currently resides in Bengaluru, India, with his wife and son
Read more about Manu Joseph