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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Idioma: Inglés
Publicado por Packt Publishing 9/29/2018, 2018
ISBN 10: 178961774X ISBN 13: 9781789617740
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 45,87
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Añadir al carritoPaperback or Softback. Condición: New. Mastering Predictive Analytics with scikit-learn and TensorFlow: Implement machine learning techniques to build advanced predictive models using Pytho. Book.
Idioma: Inglés
Publicado por Packt Publishing 2018-09-29, 2018
ISBN 10: 178961774X ISBN 13: 9781789617740
Librería: Chiron Media, Wallingford, Reino Unido
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: moluna, Greven, Alemania
EUR 42,15
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. In this book, you will find a range of methods to improve the performance of almost any predictive model, from ensemble methods to dimensionality reduction and cross-validation. You will learn the tools to produce advanced predictive models. In addition, yo.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Learn advanced techniques to improve the performance and quality of your predictive modelsKey Features: Use ensemble methods to improve the performance of predictive analytics models Implement feature selection, dimensionality reduction, and cross-validation techniques Develop neural network models and master the basics of deep learningBook Description:Python is a programming language that provides a wide range of features that can be used in the field of data science. Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations of ensemble methods, how they are used with real-world datasets, and how they improve prediction accuracy in classification and regression problems.This book starts with ensemble methods and their features. You will see that scikit-learn provides tools for choosing hyperparameters for models. As you make your way through the book, you will cover the nitty-gritty of predictive analytics and explore its features and characteristics. You will also be introduced to artificial neural networks and TensorFlow, and how it is used to create neural networks. In the final chapter, you will explore factors such as computational power, along with improvement methods and software enhancements for efficient predictive analytics.By the end of this book, you will be well-versed in using deep neural networks to solve common problems in big data analysisWhat You Will Learn: Use ensemble algorithms to obtain accurate predictions Apply dimensionality reduction techniques to combine features and build better models Choose the optimal hyperparameters using cross-validation Implement different techniques to solve current challenges in the predictive analytics domain Understand various elements of deep neural network (DNN) models Implement neural networks to solve both classification and regression problemsWho this book is for:Mastering Predictive Analytics with scikit-learn and TensorFlow is for data analysts, software engineers, and machine learning developers who are interested in implementing advanced predictive analytics using Python. Business intelligence experts will also find this book indispensable as it will teach them how to progress from basic predictive models to building advanced models and producing more accurate predictions. Prior knowledge of Python and familiarity with predictive analytics concepts are assumed.