You're reading from Modern Time Series Forecasting with Python

Product typeBook

Published inNov 2022

PublisherPackt

ISBN-139781803246802

Edition1st Edition

Concepts

Data Science

Author (1)

Manu Joseph

Learning From Data by Yaser Abu-Mostafa: https://work.caltech.edu/lectures.html.
Curse of Dimensionality – Georgia Tech: https://www.youtube.com/watch?v=OyPcbeiwps8.
Dummy Variable Trap: https://www.learndatasci.com/glossary/dummy-variable-trap/.
Using deep learning to learn categorical embeddings: https://pytorch-tabular.readthedocs.io/en/latest/tutorials/03-Extracting%20and%20Using%20Learned%20Embeddings/.
Handling categorical features – CatBoost: https://catboost.ai/en/docs/concepts/algorithm-main-stages_cat-to-numberic.
Exploring Bayesian Optimization – from Distil.pub: https://distill.pub/2020/bayesian-optimization/.
Frazier, P.I. (2018). A Tutorial on Bayesian Optimization. arXiv:1807.02811 [stat.ML]: https://arxiv.org/abs/1807.02811.
Time series clustering using tslearn: https://tslearn.readthedocs.io/en/stable/user_guide/clustering...

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Modern Time Series Forecasting with Python

Published in: Nov 2022Publisher: PacktISBN-13: 9781803246802

Author (1)

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
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