TensorFlow: Powerful Predictive Analytics with TensorFlow

This is the code repository for TensorFlow: Powerful Predictive Analytics with TensorFlow , published by Packt.

Predict valuable insights of your data with TensorFlow

What is this book about?

• Learn TensorFlow features in a real-life problem, followed by detailed TensorFlow installation and configuration
• Explore computation graphs, data, and programming models also get an insight into an example of implementing linear regression model for predictive analytics
• Solve the Titanic survival problem using logistic regression, random forests, and SVMs for predictive analytics
• Dig deeper into predictive analytics and find out how to take advantage of it to cluster records belonging to the certain group
  or class for a dataset of unsupervised observations
• Learn several examples of how to apply reinforcement learning algorithms for developing predictive models on real-life datasets

This book covers the following exciting features: 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.

If you feel this book is for you, get your copy today!

Instructions and Navigations

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

Following is what you need for this book: This book is aimed at 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.

Get to Know the Author

Md. Rezaul Karim has more than 8 years of experience in the area of research and development with a solid knowledge of algorithms and data structures in C/C++, Java, Scala, R, and Python focusing Big Data technologies: Spark, Kafka, DC/OS, Docker, Mesos, Zeppelin, Hadoop, and MapReduce and Deep Learning technologies: TensorFlow, DeepLearning4j and H2O-Sparking Water. His research interests include Machine Learning, Deep Learning, Semantic Web/Linked Data, Big Data, and Bioinformatics. He is a research scientist at Fraunhofer FIT, Germany. He is also a Ph.D. candidate at the RWTH Aachen University, Aachen, Germany. He holds a BSc and an MSc degree in Computer Science. Before joining the Fraunhofer FIT, he had been working as a researcher at Insight Centre for Data Analytics, Ireland. Before that, he worked as a lead engineer with Samsung Electronics' distributed R&D Institutes in Korea, India, Vietnam, Turkey, and Bangladesh. Before that, he worked as a research assistant in the Database Lab at Kyung Hee University, Korea. He also worked as an R&D engineer with BMTech21 Worldwide, Korea. Even before that, he worked as a software engineer with i2SoftTechnology, Dhaka, Bangladesh. He is the author of the following book titles with Packt Publishing:

Other books by the authors

Large Scale Machine Learning with Spark

Scala and Spark for Big Data Analytics

Predictive Analytics with TensorFlow

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