Named Entity Recognition is the most important, or I would say, the starting step in Information Retrieval. Information Retrieval is the technique to extract important and useful information from unstructured raw text documents. Named Entity Recognition NER works by locating and identifying the named entities present in unstructured text into…

“ spaCy” is designed specifically for production use. It helps you build applications that process and “understand” large volumes of text. It can be used to build information extraction or natural language understanding systems or to pre-process text for deep learning. …

Bayes Theorem is the extension of Conditional probability. Conditional probability helps us to determine the probability of A given B, denoted by P(A|B). So Bayes’ theorem says if we know P(A|B) then we can determine P(B|A), given that P(A) and P(B) are known to us.

In this post, I am…

As the name suggests, Conditional Probability is the probability of an event under some given condition. And based on the condition our sample space reduces to the conditional element.

For example, find the probability of a person subscribing for the insurance given that he has taken the house loan. …

Principal Component Analysis or PCA is a widely used technique for dimensionality reduction of the large data set. Reducing the number of components or features costs some accuracy and on the other hand, it makes the large data set simpler, easy to explore and visualize. Also, it reduces the computational…

Logistic regression is the most widely used machine learning algorithm for classification problems. In its original form, it is used for binary classification problem which has only two classes to predict. However, with little extension and some human brain, logistic regression can easily be used for a multi-class classification problem…