Getting Intuition behind the implementation of Naive Bayes Classifier with SMS spam collection data.

subtitle-based film similarities

Linguistic database collection for the revitalization of Cameroonian local languages and speech recognition

Multinomial classification tasks in Reddit

Determining movie genres based on synopses, using various NLP methods.

This is a Project Assignment where I have Learned to Classify the Different Texts Using Clustering Techniques. Natural Language Processing and Clustering both of these Concepts are Being Used. I have Used K-means Clustering Techniques to Implement the Problem.

Chat-Who is an Chatbot built using the concepts of NLP and CNN.

Given the title of a fake news article A and the title of a coming news article B, program classifies B into agree, disagree, and unrelated.

Intent classification is the automatic categorization of text data based on customer goals. It is known to be a complex problem in NLP. Sequence Labelling aims to classify each token (word) in a class space C. This project addresses these two problem statements by covering the basic concepts of NLP to advanced ones. For instance, linguistics ana…

Predicts the rating of a review on a scale of 0 to 5 using NLP(bag of words ML Model)

Classifying Reddit comments that are about physics, chemistry and biology using NLTK

Given the title of a fake news article A and the title of a coming news article B, program classifies B into agree, disagree, and unrelated.

Bag of words preprocessing for a set of labeled web pages

A natural language processing and machine learning project that predicts spam messages and explains how it does so

Asuna is a healthcare chatbot use to diagnose diseases via symptoms with a simple to use interface for both admins and users

Exploration of Amazon Reviews from the Electronics category through Topic Modeling using Latent Dirichlet Allocation.

Web app that implements Bag of Words algorithm

Applied Machine Learning projects includes: a supervised machine learning model to classify emails from the given dataset as spam and not-spam. 2.

The objective of this analysis is to better understand the characteristics of Detroit Schools with elevated lead levels as identified via testing in 2016 by aggregating three publicly available data sources from the city of Detroit.