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Python: Deeper Insights into Machine Learning: Leverage benefits of machine learning techniques using Python

Python: Deeper Insights into Machine Learning: Leverage benefits of machine learning techniques using Python

Python: Deeper Insights into Machine Learning: Leverage benefits of machine
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Python: Deeper Insights into Machine Learning: Leverage benefits of machine learning techniques using Python Paperback - 2017

by Raschka, Sebastian

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  • Title Python: Deeper Insights into Machine Learning: Leverage benefits of machine learning techniques using Python
  • Author Raschka, Sebastian
  • Binding Paperback
  • Condition New
  • Pages 916
  • Volumes 1
  • Language ENG
  • Publisher Packt Publishing
  • Publication date 2017-06-29
  • Bookseller's Inventory # 29987643-n
  • ISBN 9781787128576 / 1787128571
  • Weight 3.4 lbs (1.54 kg)
  • Dimensions 9.25 x 7.5 x 1.81 in (23.50 x 19.05 x 4.60 cm)
  • Category Computers - Languages / Programming
  • Quantity available 5

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Reader reviews for Python: Deeper Insights into Machine Learning: Leverage benefits of machine learning techniques using Python

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About the author

Hearty John

John Hearty is a Manager of Data Science team with substantial expertise in data science and infrastructure engineering. Having started out in mobile gaming, he was drawn to the challenge of AAA console analytics. Keen to start putting advanced machine learning techniques into practice, he signed on with Microsoft to develop player modelling capabilities and big data infrastructure at an Xbox studio. His team made significant strides in engineering and data science that were replicated across Microsoft Studios. Some of the more rewarding initiatives he led included player skill modelling in asymmetrical games, and the creation of player segmentation models for individualized game experiences. Eventually, John struck out on his own as a consultant offering a comprehensive infrastructure and analytics solutions for international client teams seeking new insights or data-driven capabilities. His favorite current engagement involves creating predictive models and quantifying the importance of user connections for a popular social network. After years spent working with data, John is largely unable to stop asking questions. In his own time, he routinely builds ML solutions in Python to fulfill a broad set of personal interests. These include a novel variant on the StyleNet computational creativity algorithm and solutions for algo-trading and geolocation-based recommendationRaschka Sebastian

Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. As Lead AI Educator at Grid AI, Sebastian plans to continue following his passion for helping people get into machine learning and artificial intelligence.Julian David

David Julian is a freelance technology consultant and educator. He has worked as a consultant for government, private, and community organizations on a variety of projects, including using machine learning to detect insect outbreaks in controlled agricultural environments (Urban Ecological Systems Ltd., Bluesmart Farms), designing and implementing event management data systems (Sustainable Industry Expo, Lismore City Council), and designing multimedia interactive installations (Adelaide University). He has also written Designing Machine Learning Systems With Python for Packt Publishing and was a technical reviewer for Python Machine Learning and Hands-On Data Structures and Algorithms with Python - Second Edition, published by Packt.

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