Statistics machine learning techniques di dangeti pratap (8 risultati)
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Condizione: good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Good condition! Any other included accessories are also in Good condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear.
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Taschenbuch. Condizione: Neu. Statistics for Machine Learning | Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R | Pratap Dangeti | Taschenbuch | Kartoniert / Broschiert | Englisch | 2017 | Packt Publishing | EAN 9781788295758 | Verantwortliche Person für die EU: Libri GmbH,…Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: 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 fo…r 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 tobuild modelsUnderstand the major differences and parallels between the statistical way and the machine learning way to solve problemsLearn how to prepare data and feed models by using the appropriate machine learning algorithms from the more-than-adequate R and Python packagesAnalyze the results and tune the model appropriately to your own predictive goalsUnderstand the concepts of the statistics required for machine learningIntroduce yourself to necessary fundamentals required for building supervised and unsupervised deep learning modelsLearn reinforcement learning and its application in the field of artificial intelligence domainWho 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.
