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Hands-On Predictive Analytics with Python

You're reading from   Hands-On Predictive Analytics with Python Master the complete predictive analytics process, from problem definition to model deployment

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789138719
Length 330 pages
Edition 1st Edition
Languages
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Author (1):
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Alvaro Fuentes Alvaro Fuentes
Author Profile Icon Alvaro Fuentes
Alvaro Fuentes
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Table of Contents (11) Chapters Close

Preface 1. The Predictive Analytics Process FREE CHAPTER 2. Problem Understanding and Data Preparation 3. Dataset Understanding – Exploratory Data Analysis 4. Predicting Numerical Values with Machine Learning 5. Predicting Categories with Machine Learning 6. Introducing Neural Nets for Predictive Analytics 7. Model Evaluation 8. Model Tuning and Improving Performance 9. Implementing a Model with Dash 10. Other Books You May Enjoy

Introducing TensorFlow and Keras

Now we know that neural networks are a special type of machine learning model. Although, usually these models need huge amounts of data to start outperforming other machine learning approaches, one big advantage is that the process of training neural networks can make use of parallelization in hardware such as graphical processing units (GPUs), which do the operations needed for training neural networks faster than traditional CPUs. This is the reason that in the past few years, new specialized software frameworks have been developed with the capacity to make use of GPUs; examples of these frameworks are Theano, Caffe, and TensorFlow. These frameworks have allowed the deep learning models to be used for professionals outside specialized academic circles, thus democratizing the use of these powerful models. In this section, we introduce the two...

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