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You're reading from  Hands-On Mathematics for Deep Learning

Product typeBook
Published inJun 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781838647292
Edition1st Edition
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Author (1)
Jay Dawani
Jay Dawani
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Jay Dawani

Jay Dawani is a former professional swimmer turned mathematician and computer scientist. He is also a Forbes 30 Under 30 Fellow. At present, he is the Director of Artificial Intelligence at Geometric Energy Corporation (NATO CAGE) and the CEO of Lemurian Labs - a startup he founded that is developing the next generation of autonomy, intelligent process automation, and driver intelligence. Previously he has also been the technology and R&D advisor to Spacebit Capital. He has spent the last three years researching at the frontiers of AI with a focus on reinforcement learning, open-ended learning, deep learning, quantum machine learning, human-machine interaction, multi-agent and complex systems, and artificial general intelligence.
Read more about Jay Dawani

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Summary

In this chapter, we learned about various forms of regression, such as (multiple) linear regression, polynomial regression, logistic regression, and softmax regression. Each of these models has aided us in figuring out the relationship that exists between one or more independent variable(s) and a dependent variable. For some of you, these concepts may seem very rudimentary, but they will serve us well on our journey throughout this book and in gaining a deeper understanding of the concepts to come.

In the next chapter, we will learn about feedforward neural networks.

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Hands-On Mathematics for Deep Learning
Published in: Jun 2020Publisher: PacktISBN-13: 9781838647292

Author (1)

author image
Jay Dawani

Jay Dawani is a former professional swimmer turned mathematician and computer scientist. He is also a Forbes 30 Under 30 Fellow. At present, he is the Director of Artificial Intelligence at Geometric Energy Corporation (NATO CAGE) and the CEO of Lemurian Labs - a startup he founded that is developing the next generation of autonomy, intelligent process automation, and driver intelligence. Previously he has also been the technology and R&D advisor to Spacebit Capital. He has spent the last three years researching at the frontiers of AI with a focus on reinforcement learning, open-ended learning, deep learning, quantum machine learning, human-machine interaction, multi-agent and complex systems, and artificial general intelligence.
Read more about Jay Dawani