Book Image

TensorFlow: Powerful Predictive Analytics with TensorFlow

By : Md. Rezaul Karim
Book Image

TensorFlow: Powerful Predictive Analytics with TensorFlow

By: Md. Rezaul Karim

Overview of this book

Predictive analytics discovers hidden patterns from structured and unstructured data for automated decision making in business intelligence. Predictive decisions are becoming a huge trend worldwide, catering to wide industry sectors by predicting which decisions are more likely to give maximum results. TensorFlow, Google’s brainchild, is immensely popular and extensively used for predictive analysis. This book is a quick learning guide on all the three types of machine learning, that is, supervised, unsupervised, and reinforcement learning with TensorFlow. This book will teach you predictive analytics for high-dimensional and sequence data. In particular, you will learn the linear regression model for regression analysis. You will also learn how to use regression for predicting continuous values. You will learn supervised learning algorithms for predictive analytics. You will explore unsupervised learning and clustering using K-meansYou will then learn how to predict neighborhoods using K-means, and then, see another example of clustering audio clips based on their audio features. This book is ideal for developers, data analysts, machine learning practitioners, and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. This book is repurposed for this specific learning experience from material from Packt's Predictive Analytics with TensorFlow by Md. Rezaul Karim.
Table of Contents (8 chapters)
TensorFlow: Powerful Predictive Analytics with TensorFlow

Chapter 1. From Data to Decisions – Getting Started with TensorFlow

Despite the huge availability of data and significant investments, many business organizations still go on gut feel because they neither make the proper use of the data nor do they take appropriate and effective business decisions. TensorFlow, on the other hand, can be used to help take the business decision from this huge collection of data. TensorFlow is mathematical software and an open source software library for Machine Intelligence, developed in 2011 by the Google Brain Team and it can be used to help us analyze data to predict the effective business outcome. Although the initial target of TensorFlow was to conduct research in machine learning and in deep neural networks, however, the system is general enough to be applicable in a wide variety of other domains as well.

Keeping in mind your needs and based on all the latest and exciting features of TensorFlow 1.x, in this lesson, we will give a description of the main TensorFlow capabilities that are mostly motivated by a real-life example using the data.

The following topics will be covered in this lesson:

  • From data to decision: Titanic example

  • General overview of TensorFlow

  • Installing and configuring TensorFlow

  • TensorFlow computational graph

  • TensorFlow programming model

  • TensorFlow data model

  • Visualizing through TensorBoard

  • Getting started with TensorFlow: linear regression and beyond