Predictive Analytics with TensorFlow

Predictive Analytics with TensorFlow

By : Md. Rezaul Karim

Buy this Book

Predictive Analytics with TensorFlow

By: Md. Rezaul Karim

Buy this Book

Overview of this book

Predictive analytics discovers hidden patterns from structured and unstructured data for automated decision-making in business intelligence. This book will help you build, tune, and deploy predictive models with TensorFlow in three main sections. The first section covers linear algebra, statistics, and probability theory for predictive modeling. The second section covers developing predictive models via supervised (classification and regression) and unsupervised (clustering) algorithms. It then explains how to develop predictive models for NLP and covers reinforcement learning algorithms. Lastly, this section covers developing a factorization machines-based recommendation system. The third section covers deep learning architectures for advanced predictive analytics, including deep neural networks and recurrent neural networks for high-dimensional and sequence data. Finally, convolutional neural networks are used for predictive modeling for emotion recognition, image classification, and sentiment analysis.

Predictive Analytics with TensorFlow

Credits

About the Author

Acknowledgments

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

Free Chapter

Basic Python and Linear Algebra for Predictive Analytics

A basic introduction to predictive analytics

A bit of linear algebra

Installing and getting started with Python

Getting started with Python

Vectors, matrices, and graphs

Span and linear independence

Principal component analysis

Singular value decomposition

Predictive analytics tools in Python

Summary

Statistics, Probability, and Information Theory for Predictive Modeling

Using statistics in predictive modeling

Basic probability for predictive modeling

Using information theory in predictive modeling

Summary

From Data to Decisions – Getting Started with TensorFlow

Taking decisions based on data - Titanic example

General overview of TensorFlow

Installing and configuring TensorFlow

TensorFlow computational graph

TensorFlow programming model

Data model in TensorFlow

TensorBoard

Getting started with TensorFlow – linear regression and beyond

Summary

Putting Data in Place - Supervised Learning for Predictive Analytics

Supervised learning for predictive analytics

Linear regression - revisited

From disaster to decision - Titanic example revisited

Summary

Clustering Your Data - Unsupervised Learning for Predictive Analytics

Unsupervised learning and clustering

Using K-means for predictive analytics

Predictive models for clustering audio files

Using kNN for predictive analytics

Summary

Predictive Analytics Pipelines for NLP

NLP analytics pipelines

Transformers and estimators

Using BOW for predictive analytics

TF-IDF model for predictive analytics

Using Word2vec for sentiment analysis

Summary

Using Deep Neural Networks for Predictive Analytics

Deep learning for better predictive analytics

Artificial Neural Networks

Deep Neural Networks

Multilayer perceptrons

DNN performance analysis

Fine-tuning DNN hyperparameters

Using multilayer perceptrons for predictive analytics

Deep belief networks

Using deep belief networks for predictive analytics

Summary

Using Convolutional Neural Networks for Predictive Analytics

CNNs and the drawbacks of regular DNNs

CNN architecture

Convolutional operations

Pooling layer and padding operations

Tuning CNN hyperparameters

CNN-based predictive model for sentiment analysis

CNN model for emotion recognition

CNN predictive model for image classification

Summary

Using Recurrent Neural Networks for Predictive Analytics

RNN architecture

Using BRNN for image classification

Implementing an RNN for spam prediction

Developing a predictive model for time series data

An LSTM predictive model for sentiment analysis

Summary

Recommendation Systems for Predictive Analytics

Recommendation systems

Collaborative filtering approach for movie recommendations

Factorization machines for recommendation systems

Improved factorization machines for predictive analytics

Summary

Using Reinforcement Learning for Predictive Analytics

Reinforcement learning

Reinforcement learning in predictive analytics

Notation, policy, and utility in RL

Developing a multiarmed bandit's predictive model

Developing a stock price predictive model

Summary

Index

Customer Reviews

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Predictive Analytics with TensorFlow

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: October 2017

Production reference: 1251017

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78839-892-3

Predictive Analytics with TensorFlow

By : Md. Rezaul Karim

Predictive Analytics with TensorFlow

By: Md. Rezaul Karim

Overview of this book

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