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Descriptive Analysis — Machine Learning

Descriptive Analysis is an extremely useful process Businesses in Data Analysis and Machine Learning

Descriptive Analysis in Machine Learning is all about perspective to understand the data and its different existing patterns. Basically, it is part of four types of Data Analysis concepts. Descriptive Analysis mainly tends more towards unsupervised learning for outlining, classifying, and drawing out information to get the answers for what had happened in past. It also helps people in the proper understanding of certain scenarios and its outcome. Thus helping them to take proper decisions related to business. Actually, it is one of the simplest and easiest ones to understand and implement with the help of a number of available tools and minimum skills. Hence it is quite beneficial for AI Startups to analyze their business. Also, it is extremely useful in recognizing the structure of data, and different patterns of data.

Different Categories of Descriptive Analysis

Descriptive Analysis is normally differentiated into groups. Now we shall be having a look at them,

  • Operational Reports

Operational Reports in simple words would be the report card of an organization. Which is helpful in understanding the past working and performance of a certain organization.

  • Statistical Reports

Statistical Reports are nothing but reports that show data of an organization in a statistical form which is often easy to understand compare with past and present outcomes. To represent statistical reports various statistical analysis methods are used.

  • Data Mining approaches

Data mining is all about extracting exact data from different unknown data patterns. Basically, it is discovery processes of data that are useful in understanding different properties of data.

Hence we can conclude that Descriptive Analysis is an extremely useful initial process in Data analysis. And its application in different Data Analysis techniques is always fruitful.



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