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Supervised Learning with Linear Regression

By: Stephen Donald Huff
Narrated by: Harriett Hunt
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Publisher's Summary

This course provides a detailed executive-level review of contemporary topics in supervised machine learning theory with specific focus on predictive modeling and linear regression.

The ideal student is a technology professional with a basic working knowledge of machine learning theory.  

Additionally, to better inform the interested student, the final lesson of this course presents samples in Python describing the essential implementation of described regression methods.

To reduce space and improve clarity, this code targets a basic Keras environment - this inclusion is not meant as an endorsement of one system over another (all provide benefits); instead, at the time of this writing, Keras simply offers a popular, facile ‘front end’ for managing TensorFlow, Microsoft Cognitive Toolkit, and Theano deep learning systems, all using this popular script.

©2018 Stephen Donald Huff (P)2019 Stephen Donald Huff

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