Final Year project based upon Network Intrusion Detection System

Text classification on job description dataset

The objective of this project is to classify whether upcoming product will have positive or negative Sentiment.

Sentiment Analysis of Movie Reviews is either positive or negative review, the dataset which is used is "IMDB Dataset of 50K Movie Reviews" and the machine learning algorithm which I used in this is Logistic Regression , Random Forest and LinearSVC.

Object Detection Techniques for the Vehicle Detection

Application of various text classification algorithms on multiple datasets.

This project involves the implementation of efficient and effective LinearSVC on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

This repository contains a number of experiments with Multi Lingual Transformer models (Multi-Lingual BERT, DistilBERT, XLM-RoBERTa, mT5 and ByT5) focussed on the Dutch language.

Arabic_Dialect_Identification_NLP-AIM-Task

Implementation of various Machine Learning and Deep Learning models for Sentiment Analysis on the 'Sentiment Labelled Sentences Data Set' by University of California, Irvine.

In this project I intend to predict customer churn on bank data.

Fake news detection using TF-IDF vectorization and LinearSVC

Part of an internal project for my internship

Scraping data through Instagram and using the data to build a predictive model

Developed a project which detects the news either as fake or real. GPT2 transformer model is used to predict the sentiment and genre of news. Classifier Machine Learning models and Hugging Face Transformer-Based language models are used to classify the news

Implementation of Drug database with LinearSVC, BernoulliNB, MultinomialNB, LogisticRegression, Perceptron and MLPClassifier models

Erdos Institute Bootcamp project analyzing cuisines by recipe ingredient lists.

Dartmouth COSC 274: Machine Learning models for Amazon Reviews dataset

A mini ML project of feature and model selection on breast cancer data

NLP Classification and Clustering with spam SMS dataset