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Statistics for Machine Learning: Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R
Seller: Goodwill of Silicon Valley, SAN JOSE, CA, U.S.A.
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Condition: acceptable. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Acceptable condition! Any other included accessories are also in Acceptable condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear such as cover tears discoloration, staining, marks, scuffs, etc. All pages intact.
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Numerical Computing with Python (Paperback or Softback)
Published by Packt Publishing 12/19/2018, 2018
ISBN 10: 1789953634 ISBN 13: 9781789953633
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Statistics for Machine Learning (Paperback or Softback)
Published by Packt Publishing 7/21/2017, 2017
ISBN 10: 1788295757 ISBN 13: 9781788295758
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Statistics for Machine Learning: Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R
Published by Packt Publishing 2017-07, 2017
ISBN 10: 1788295757 ISBN 13: 9781788295758
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Numerical Computing with Python
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Statistics for Machine Learning: Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R
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Statistics for Machine Learning
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Numerical Computing with Python
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Statistics for Machine Learning
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Numerical Computing with Python
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Add to basketCondition: New. Über den AutorrnrnPratap Dangeti develops machine learning and deep learning solutions for structured, image, and text data at TCS, analytics and insights, innovation lab in Bangalore. He has acquired a lot of experience in both analytics a.
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Statistics for Machine Learning Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R
Published by Packt Publishing Limited, 2017
ISBN 10: 1788295757 ISBN 13: 9781788295758
Language: English
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Statistics for Machine Learning Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R
Published by Packt Publishing Limited, 2017
ISBN 10: 1788295757 ISBN 13: 9781788295758
Language: English
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Numerical Computing with Python
Published by Packt Publishing Limited, 2018
ISBN 10: 1789953634 ISBN 13: 9781789953633
Language: English
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Numerical Computing with Python
Published by Packt Publishing Limited, 2018
ISBN 10: 1789953634 ISBN 13: 9781789953633
Language: English
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Statistics For Machine Learning
Published by Packt Publishing, Limited, 2017
ISBN 10: 1788295757 ISBN 13: 9781788295758
Language: English
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Statistics for Machine Learning
Published by Packt Publishing Limited, 2017
ISBN 10: 1788295757 ISBN 13: 9781788295758
Language: English
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Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 795.
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Build Machine Learning models with a sound statistical understanding. Key Features:Learn about the statistics behind powerful predictive models with p-value, ANOVA, and F- statistics. Implement statistical computations programmatically for supervised and unsupervised learning through K-means clustering. Master the statistical aspect of Machine Learning with the help of this example-rich guide to R and Python. Book Description: Complex statistics in machine learning worry a lot of developers. Knowing statistics helps you build strong machine learning models that are optimized for a given problem statement. This book will teach you all it takes to perform the complex statistical computations that are required for machine learning. You will gain information on the statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. You will see real-world examples that discuss the statistical side of machine learning and familiarize yourself with it. You will come across programs for performing tasks such as modeling, parameter fitting, regression, classification, density collection, working with vectors, matrices, and more. By the end of the book, you will have mastered the statistics required for machine learning and will be able to apply your new skills to any sort of industry problem. What You Will Learn:Understand the statistical and machine learning fundamentals necessary to build models Understand the major differences and parallels between the statistical way and the machine learning way to solve problems Learn how to prepare data and feed models by using the appropriate machine learning algorithms from the more-than-adequate R and Python packages Analyze the results and tune the model appropriately to your own predictive goals Understand the concepts of the statistics required for machine learning Introduce yourself to necessary fundamentals required for building supervised and unsupervised deep learning models Learn reinforcement learning and its application in the field of artificial intelligence domain Who this book is for: This book is intended for developers with little to no background in statistics, who want to implement Machine Learning in their systems. Some programming knowledge in R or Python will be useful.
