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Mastering Predictive Analytics with scikit-learn and TensorFlow
Mastering Predictive Analytics with scikit-learn and TensorFlow

Mastering Predictive Analytics with scikit-learn and TensorFlow: Implement machine learning techniques to build advanced predictive models using Python

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Profile Icon Alvaro Fuentes
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Paperback Sep 2018 154 pages 1st Edition
eBook
Mex$541.99
Paperback
Mex$676.99
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Free Trial
Arrow left icon
Profile Icon Alvaro Fuentes
Arrow right icon
Free Trial
Paperback Sep 2018 154 pages 1st Edition
eBook
Mex$541.99
Paperback
Mex$676.99
Subscription
Free Trial
eBook
Mex$541.99
Paperback
Mex$676.99
Subscription
Free Trial

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Mastering Predictive Analytics with scikit-learn and TensorFlow

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Key benefits

  • 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 learning

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 analysis.

Who is this book 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.

What 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 problems

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Sep 29, 2018
Length: 154 pages
Edition : 1st
Language : English
ISBN-13 : 9781789617740
Category :
Languages :

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Product Details

Publication date : Sep 29, 2018
Length: 154 pages
Edition : 1st
Language : English
ISBN-13 : 9781789617740
Category :
Languages :

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Frequently bought together


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Total Mex$ 2,358.97
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Mastering Predictive Analytics with scikit-learn and TensorFlow
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Total Mex$ 2,358.97 Stars icon
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Table of Contents

5 Chapters
Ensemble Methods for Regression and Classification Chevron down icon Chevron up icon
Cross-validation and Parameter Tuning Chevron down icon Chevron up icon
Working with Features Chevron down icon Chevron up icon
Introduction to Artificial Neural Networks and TensorFlow Chevron down icon Chevron up icon
Predictive Analytics with TensorFlow and Deep Neural Networks Chevron down icon Chevron up icon
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