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All about Covariance in Data Science
This blog aims to explain the Covariance which is a very important topic in Feature Engineering in Data Science. In addition to that, this blog will also cover its use-cases, advantages & disadvantages.
Data Science is a very hot topic at present. Most of the pursuing students are selecting this field as their profession, in addition to that, many corporate guys are also shifting towards this technology by seeing the scope of this field.
Since Data Science is very much famous & a hot topic, that is why it is attracting most people which is an amazing thing, but in contrary to that, most of the guys, when they start learning in this field, they have a feeling to learn it as soon as possible. But, Data Science is a very much vast field, it can be considered as an ocean of different concepts which has to be understood clearly in order to excel in this field.
The major problem with most of the people is that they do not try to understand the concepts, & as a consequence of this most of the concepts are missed in the field like Data Science, moreover the concepts which are learned, are also not properly understood.
Because of this learning approach, most of the people remember to find the correlation while doing the Feature Selection, but they didn’t even know where Feature Selection lies in Data Science Pipeline. In addition to that, while finding the correlation, various techniques are a must learn, so that one could understand why a particular technique is applied at the moment? why not others? What is the drawback of the other techniques?
This blog will cover everything related to the Covariance from its internal working to significance to its use-cases.
An In-Depth Introduction to Covariance!
Covariance is an integral technique to find the correlation between the features of a dataset. Covariance is actually a Feature Selection technique that is in turn a part of Feature Engineering.
Correlation
It signifies the similarities between the features, or it can be understood as the dependency…
