TFIDF being the most basic and simple topic in NLP, there's alot that can be done using TFIDF only! So, in this repo, I'll be adding the blog, TFIDF basics, wonders done using tfidf etc.

Phony News Classifier is a repository which contains analysis of a natural language processing application i.e fake news classifier with the help of various text preprocessing strategies like bag of words,tfidf vectorizer,lemmatization,Stemming with Naive bayes and other deep learning RNN (LSTM) and maintaining the detailed accuracy below

This webapp helps to find the inaccurate information around the world through news

Application of VMD in NLP via TF-IDF for better semantic relationships.

Hire the Perfect candidate. HackerEarth Competitions solution.

Posts/Feeds recommendation engine based on content based and collaborative filtering methods

Program that can take in large amounts of .csv files in the same directory and trains a deep learning neural network model based on the best/worst students evaluated by the user. Second program then utilizes the model from the first program to produce a projected report for each individual student inputted.

Use Key NLP techniques to classify news articles into categories: Bag_of_Words (tf-Idf), word embeddings and BERT language model

🤖 Sentiment Analysis using IMDb Reviews. The project contains TfidfVectorizer for representing text in numeric form. 🎥

A machine learning model for detecting fake news

The aim - is to develop a model that will give accurate predictions for the customer's test sample, but the training sample for is not given. It should be collected by parsing

Steam recommendation system

Fake new detection using text classification as real or fake news segments. Required installations - Python 3.8, NLTK, Scikit-Learn, Jupyter. Text cleaning, tokenization, vectorization, classification model generation and evaluation.

Movie recommendation system using TfidfVectorizer, NearestNeighbors

feature extraction, Vectorization, similarity scores, finding closest match to user input, find index, enumerate similarity, give recommendations.

In this project we are comparing two approaches for movie recommendation for a new user or existing user based on their age, gender, occupation.

This project is a Python-based data science end-to-end chatbot designed to autonomously handle conversations without the need for human intervention. Leveraging advanced natural language processing (NLP) techniques and machine learning algorithms, the chatbot is capable of understanding user queries, providing relevant responses.

Amazon reviews Sentiment Analysis