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Supervised Learning with Linear Regression: An Executive Review of Hot Technology
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 ‘frontend’ for managing TensorFlow or Microsoft Cognitive Toolkit deep learning systems, all using this popular script.
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 ‘frontend’ for managing TensorFlow or Microsoft Cognitive Toolkit deep learning systems, all using this popular script.
158 pages, Kindle Edition
Published October 24, 2018
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