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

What the electronic brain does best


As the processing power increases with computers, the electronic brain—or computers—are much better when compared to the human brain in some aspects, as we will explore in the following sections.

Speed information storage

The electronic brain (computers) can read and store high volumes of information at enormous speeds. Storage capacity is exponentially increasing. The information is easily replicated and transmitted from one place to another. The more information we have at our disposal for analysis, pattern, and model formation, the more accurate our predictions will be, and the machines will be much more intelligent. Information storage speed is consistent across machines when all factors are constant. However, in the case of the human brain, storage and processing capacities vary based on individuals.

Processing by brute force

The electronic brain can process information using brute force. A distributed computing system can scan/sort/calculate and run various types of compute on very large volumes of data within milliseconds. The human brain cannot match the brute force of computers. 

Computers are very easy to network and collaborate with in order to increase collective storage and processing power. The collective storage can collaborate in real time to produce intended outcomes. While human brains can collaborate, they cannot match the electronic brain in this aspect.