Vector Representations of Words

One of the most significant advancements in the field of Natural Language Processing (NLP) over the past decade has been the development and adoption of vector representations…

Unigram Models

A Unigram model is a type of language model that considers each token to be independent of the tokens before it. It’s the simplest language model, in…

Word2Vec

Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec…

Bigram Models

A Bigram model is a language model in which we predict the probability of the correctness of a sequence of words by just predicting the occurrence of the…

Term Frequency-Inverse Document Frequency (TF-IDF)

TF-IDF is a natural language processing (NLP) technique that’s used to evaluate the importance of different words in a sentence. It’s useful in text classification and for helping…

NLP pipeline Step By Step

In Natural Language Processing (NLP), an NLP pipeline is a sequence of interconnected steps that systematically transform raw text data into a desired output suitable for further…

Lemmatization

Lemmatization is a text pre-processing technique used in natural language processing (NLP) models to break a word down to its root meaning to identify similarities. In lemmatization, rather…

Stemming

Stemming is a text preprocessing technique used in natural language processing (NLP) to reduce words to their root or base form. The goal of stemming is to…

Named Entity Recognition (NER)

Named-entity recognition is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names,…

Common Challenges and Solutions in Implementing LDA Models

LDA (Latent Dirichlet Allocation): In NLP(Natural Language Processing), Topic Modeling identifies and extracts abstract topics from large collections of text documents. It uses algorithms such as LDA…