Free eBook: Artificial Intelligence for Big Data

Artificial Intelligence for Big Data
Build next-generation Artificial Intelligence systems with Java

Anand Deshpande and Manish Kumar, 384 pages, May 2018

Key Features

  • Implement AI techniques to build smart applications using Deeplearning4j
  • Perform big data analytics to derive quality insights using Spark MLlib
  • Create self-learning systems using neural networks, NLP, and reinforcement learning


Create smart systems to extract intelligent insights for decision making. You will learn about widely used Artificial Intelligence techniques for carrying out solutions in a production-ready environment. You'll explore advanced topics such as clustering, symbolic and sub-symbolic information representation, and many more.

Register now to access this free eBook

Your password must have at least 8 characters, one uppercase, one lowercase and one number.

By signing up, you are confirming you would like to receive occasional emails about special offers and recommendations.


Chapter 1


Big Data and Artificial Intelligence Systems

Understand the concept of the results pyramid, which is a model for the continuous improvement of human life and striving to get better results with an improved understanding of the world based on data (experiences), which shape our models (beliefs).

Chapter 2


Ontology for Big Data

Explore the need for a standardized and consistent representation of the world's knowledge for the evolution of intelligent systems, and how these systems are modeled against the human brain. Ontologies, as applied to information systems, is a W3C standard that defines the generic rules for knowl...

Chapter 3


Learning from Big Data

Cover the basic concepts of machine learning algorithms and saw how the Spark programming model is an effective tool in leveraging big data assets for machine learning. With a deep dive into supervised and unsupervised algorithms, and Spark machine learning libraries.

Chapter 4


Neural Network for Big Data

Introduction to the basic building blocks of the ANNs and simple techniques to train the models in order to generalize the model for producing outcomes for the new datasets.

Chapter 5


Deep Big Data Analytics

Explore how deep learning can be utilized for addressing some important problems in big data analytics, including extracting complex patterns from massive volumes of data, semantic indexing, data tagging, fast information retrieval, and simplifying discriminative tasks such as classification.

Chapter 6


Natural Language Processing

Combining NLP with an ontological worldview, intelligent machines can derive meaning from the text based assets at the internet scale and evolve to a know-everything system that can complement the human ability to comprehend vast amounts of knowledge, and use it at the right time with the best po...

Related Titles

Django 2 by Example

Learn Django 2.0 with four end-to-end projects

Artificial Intelligence for Robotics

Bring a new degree of interconnectivity to your world by building your own intelligent robots

Learning Microsoft Cognitive Services - Third Edition

Build smarter applications with AI capabilities using Microsoft Cognitive Services APIs without much hassle

Discover the new Packt free eBook range