This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.

It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization

NLP based Classification Model that predicts a person's personality type as one of the 16 Myers Briggs personality types. Extremely challenging project dealing with correlation between human psychology and casual writing styles and handling heavily imbalanced classes. Check the app here - https://mb-predictor-motetuzs5q-uc.a.run.app/

This project employs emotion detection in textual data, specifically trained on Twitter data comprising tweets labeled with corresponding emotions. It seamlessly takes text inputs and provides the most fitting emotion assigned to it.

Engaged in research to help improve to boost text sentiment analysis using facial features from video using machine learning.

A Natural Language Processing with SMS Data to predict whether the SMS is Spam/Ham with various ML Algorithms like multinomial-naive-bayes,logistic regression,svm,decision trees to compare accuracy and using various data cleaning and processing techniques like PorterStemmer,CountVectorizer,TFIDF Vetorizer,WordnetLemmatizer. It is implemented usi…

Fake News Detection System for detecting whether news is fake or not. The model is trained using "Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection. Link for dataset: https://arxiv.org/abs/1705.00648.

Built a movie recommender system with Streamlit and deploy in Heroku Platform.

Twitter Sentiment Analysis Using InSet (Indonesia Sentiment Lexicon) and Random Forest Classifier

💉 Vaccine Sentiment Classifier is a deep learning classifier trained on real world twitter data, that distinguishes 3 types of tweets: Neutral, Anti-vax & Pro-vax.

Twitter Sentiment Analysis Using Vader Lexicon and Random Forest Classifier

Text Mining project about Sentiment Analysis of Drugs Reviews.

Scrapped tweets using twitter API (for keyword ‘Netflix’) on an AWS EC2 instance, ingested data into S3 via kinesis firehose. Used Spark ML on databricks to build a pipeline for sentiment classification model and Athena & QuickSight to build a dashboard

This project involves detecting fake news using a decision tree classifier in Jupyter Notebook. Fake news detection is an important task in the field of natural language processing and machine learning, as it helps identify and filter out misleading or false information.

A machine learning model that predicts tags for a given question and body.

Application of Machine Learning Techniques for Text Classification and Topic Modelling on CrisisLexT26 dataset.

Natural Language Processing Recipes

The document classification solution should significantly reduce the manual human effort in the HRM. It should achieve a higher level of accuracy and automation with minimal human intervention.

Spam Classifier project for my end-of-semester project for Intro to AI class. We were a group of four people. I worked on all the Naive Bayes models.

Movie Recommendation - provides user with the top choices of movie he/she wanted to watch based on their current choice