📷 Generates Text Analytics using Bag of Words. Upload your data and it will suggest the relevant Newsgroups for you.

:cake: A library for creating n-grams, skip-grams, bag of words, bag of n-grams, bag of skip-grams.

Repository for the lectures taught in the course named "Natural Language Processing" at the University of Guilan, Department of Computer Engineering.

VIP Machine Learning Exercises and Practices

A chatbot which can recommend itineraries, flights and hotels

Text classification is the task of assigning a set of predefined categories to free text. Text classifiers can be used to organize, structure, and categorize pretty much anything. For example, new articles can be organized by topics, support tickets can be organized by urgency, chat conversations can be organized by language, brand mentions can be organized by sentiment, and so on.

Oasis Infobyte Internship Data Science task-4

Analyse of election machine texts from the Finnish parliament elections 2015

Recommend similar apparel searched by user on Amazon.

Notebooks to tackle the Kaggle Spooky Author competition. The challenge is to accurately identify the author from their sentences.

Classify comments on categories - "Toxic", "Severe Toxic", "Obscene", "Threat", "Insult", "Identity Hate", "Any of the Above", "None of the Above".

Movie Recommendation using Content Filtering (Cosine Similarity) with Flask web application

Different takes at creating a content based movie recommendation system using MovieLens dataset. One approach focuses on finding the correlation between different attributes to recommend movie. Another approach make use of the bag of word model along with machine learning algorithms.

Code and projects developed in the VCOM subject throughout the semester (MIEIC 4th year, 2nd semester).

No description provided.

Performed Twitter Sentiment Analysis on 10 years of Twitter Data using bag of words approach, and predicted stock market trends using Time Series Neural Networks.

Basic Language Models , Bag of Words, Ngram Models Etc NLP modelling and associated tasks

Stock Sentimental analysis Classifier using News Headlines

Computer Vision multilabel classification with different techniques: (KNN,PCA,LDA,BOVW,SIFT,VGG16)

This repository contains implementations of text classification using a Rule-Based Classifier and Bag of Words model, as well as word embeddings using the Skip-gram model of Word2Vec. It includes detailed preprocessing steps, model training, and relevant references.

NLP on Women's Clothing Text Reviews

A chatbot is a conversational assistant that assists you with information via chat. This chatbot gives a response in both speech and text.

This repository houses a Streamlit web application for fake news detection. The app allows users to input a news article and predicts whether it is likely fake or real based on its content. It provides options to select different vectorizers (TF-IDF or Bag of Words) and classifiers (Linear SVM or Naive Bayes) to customize the prediction model.

Trained and optimized a Classification Machine Learning model to predict the grammatical flow of email using state of the art techniques : 1. Word2Vec 2. tf-idf 3. bag-of-words. The models used include Logistic Regression and Support Vector Mechanics with 250-300 features.

This Repo, explores various processes for sentiment analysis using Amazon Customer Review dataset.

A spam classifier is a software or machine learning model that categorizes incoming messages or content as either "spam" (unwanted or irrelevant) or "ham" (legitimate or relevant), using automated techniques.

Review sentiment based on drug user reviews text/ dataset, using a supervised binary text classifier, which will classify user reviews as positive or negative

Book Recommendation System (Content Based) built on Bag Of Words algorithm and integrated into a web app using streamlit

Tokenization, Stemming, Lemmatization, Bag of words, TF-IDF

This repo has bag of words, string match & fingerprinting algorithms written in Java language.