PREAMBLE
Nowadays, we all are very intimated with Siri, Alexa, and Cortana. This is very fascinating to see such machines doing a number of things like a human being. Do you ever think, how can these machines act like a human being and how could it take decisions on its own? The answer to all these questions is data science technology. All the software which are based on voice recognition are applications of data science technology. So, we should first understand, what does data science mean? What does it actually do? Basically, data science is the technology which accumulates data from the consumer and analyzes that data. The analysis of data is the most important process of data science technology. The data which is gathered from the consumer suffers different stages to give a profitable output. Data scientists are skilled and professional persons who are responsible for performing these tasks. The data is gathered from the consumer, then the useful information is grabbed from an ample amount of the data, then relevant data is selected and combined together. Data mining is the process in which data is collected from the consumer. Clustering is the process of insight into useful information from the accumulated data. Data exploration is the process of grouping relevant data from the useful data which is obtained. Data integration is the process of combining the analyzed data. So, these were some processes of data science technology which are very important. There are many more. Here, we will discuss the clustering method of data science technology.
WHAT IS CLUSTERING?
Clustering is an important process of data science technology because it is an analyzing step of the data. In the whole process of data science, from collecting data from the user to deploying it to the user, the analyzing part of the data plays a very vital role. Clustering is the process of recognizing hidden patterns of the data and analyzing them in such a way that the data gives a productive output. The analyzed data is then kept in a group which is known as a cluster. The information which is kept in clusters are again arranged in a sorted manner. The next question that arises is, on which basis are these clusters formed? The answer to this question would be clear if we cite an example of online shopping sites. The machine algorithms will recognize the shopping pattern of each and every customer on the basis of these patterns, the information which is relevant to each other are kept in one cluster. The clusters are formed on the basis of the relevant data. There are two types of clustering-->
Hard clustering
Soft clustering
In this way, clustering is used for making the business more profitable and productive.
After understanding what clustering is, many people might understand that the demand for data scientists is very high at the present time. Almost all the companies are using Data science course.
