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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Python Machine Learning Case Studies | Five Case Studies for the Data Scientist | Danish Haroon | Taschenbuch | xvii | Englisch | 2017 | Apress | EAN 9781484228227 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources.Python Machine Learning Case Studies takes you through the steps to improve business processes and determine the pivotal points that frame strategies. You'll see machine learning techniques that you can use to support your products and services. Moreover you'll learn the pros and cons of each of the machine learning concepts to help you decide which one best suits your needs.By taking a step-by-step approach to coding in Python you'll be able to understand the rationale behind model selection and decisions within the machine learning process. The bookis equipped with practical examples along with code snippets to ensure that you understand the data science approach to solving real-world problems.What You Will LearnGain insights into machine learning concepts Work on real-world applications of machine learningLearn concepts of model selection and optimizationGet a hands-on overview of Python from a machine learning point of viewWho This Book Is ForData scientists, data analysts, artificial intelligence engineers, big data enthusiasts, computer scientists, computer sciences students, and capital market analysts. 224 pp. Englisch.
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Danish Haroon currently leads the Data Sciences team at Market IQ Inc, a patented predictive analytics platform focused on providing actionable, real-time intelligence, culled from sentiment inflection points. He received his MBA from Karachi School for Bus.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Applies a case study-based approach to machine learningSpringer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 224 pp. Englisch.
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EUR 81,20
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources.Python Machine Learning Case Studies takes you through the steps to improve business processes and determine the pivotal points that frame strategies. You'll see machine learning techniques that you can use to support your products and services. Moreover you'll learn the pros and cons of each of the machine learning concepts to help you decide which one best suits your needs.By taking a step-by-step approach to coding in Python you'll be able to understand the rationale behind model selection and decisions within the machine learning process. The bookis equipped with practical examples along with code snippets to ensure that you understand the data science approach to solving real-world problems.What You Will LearnGain insights into machine learning concepts Work on real-world applications of machine learningLearn concepts of model selection and optimizationGet a hands-on overview of Python from a machine learning point of viewWho This Book Is ForData scientists, data analysts, artificial intelligence engineers, big data enthusiasts, computer scientists, computer sciences students, and capital market analysts.