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Mastering Predictive Analytics with scikit-learn and TensorFlow

You're reading from Mastering Predictive Analytics with scikit-learn and TensorFlow Implement machine learning techniques to build advanced predictive models using Python

Product type Paperback

Published in Sep 2018

Publisher Packt

ISBN-13 9781789617740

Length 154 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Author (1):

Alvaro Fuentes

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Table of Contents (7) Chapters

Preface

1. Ensemble Methods for Regression and Classification FREE CHAPTER

2. Cross-validation and Parameter Tuning

3. Working with Features

4. Introduction to Artificial Neural Networks and TensorFlow

5. Predictive Analytics with TensorFlow and Deep Neural Networks

6. Other Books You May Enjoy

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Summary

In this chapter, we talked about ANNs, deep learning, and the elements of a deep learning model. We then installed TensorFlow and learned about the core concepts that we use in TensorFlow.

In the next chapter, we will perform predictive analytics with TensorFlow and deep learning.

The rest of the chapter is locked

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Authors (1)

Alvaro Fuentes

Alvaro Fuentes

Alvaro Fuentes is a senior data scientist with a background in applied mathematics and economics. He has more than 14 years of experience in various analytical roles and is an analytics consultant at one of the ‘Big Three' global management consulting firms, leading advanced analytics projects in different industries like banking, technology, and consumer goods. Alvaro is also an author and trainer in analytics and data science and has published courses and books, such as 'Become a Python Data Analyst' and 'Hands-On Predictive Analytics with Python'. He has also taught data science and related topics to thousands of students both on-site and online through different platforms such as Springboard, Simplilearn, Udemy, and BSG Institute, among others.

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