Book Image

Artificial Intelligence for Big Data

By : Anand Deshpande, Manish Kumar
Book Image

Artificial Intelligence for Big Data

By: Anand Deshpande, Manish Kumar

Overview of this book

In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Deep reinforcement learning


In order for the reinforcement learning algorithm to be deployed in real-world use cases and scenarios, we need to leverage the power of deep neural networks, which can infer the information from the environments in a human-like manner. One of the goals of AI is to augment human capabilities by creating autonomous agents that interact with the environment in which they operate, learn optimal behaviors that improve over time, and learn from mistakes.

For example, the signals from the video camera can be interpreted using a deep neural network. Once this signal is interpreted, the objects and patterns observed by the camera can be analyzed with the help of a deep neural network, as we have seen in the chapters on artificial neural networks (ANNs). These deep neural networks can then be used for application of reinforcement learning algorithms for creating a navigation system that learns over a period of time based on the training feeds.

Fundamentally, a combination...