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

Supervised and unsupervised machine learning


Machine learning at a broad level is categorized into two types: supervised and unsupervised learning. As the name indicates, this categorization is based on the availability of the historical data or the lack thereof. In simple terms, a supervised machine learning algorithm depends on the trending data, or version of truth. This version of truth is used for generalizing the model to make predictions on the new data points.

Let's understand this concept with the following example:

Figure 3.1 Simple training data: input (independent) and target (dependent) variables

Consider that the value of the y variable is dependent on the value ofx. Based on a change in the value ofx, there is a proportionate change in the value ofy(think about any examples where the increase or decrease in the value of one factor proportionally changes the other).

Based on the data presented in the preceding table, it is clear that the value of y increases with an increase in...