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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

Summary

In this chapter, we learned the basics of Dash and showed how to deploy a model with a hands-on example. Some key points that we discussed were the model implementation phase, three main ways in which a predictive analytics report can be implemented, use of predictive analytics models, and how to use trained models to build an application.

We also learned how to use the Dash framework and Plotly library to build an application. And we learned how to provide interactivity in Dash by writing decorators in functions that take inputs and modify outputs for the application.

Finally, always keep in mind that the point of predictive analytics is to solve problems. When deploying a predictive model, think about the users of your solution first and how to build the solution that works best for them.

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