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Final Year project based upon Network Intrusion Detection System
The objective of this project is to classify whether upcoming product will have positive or negative Sentiment.
Text classification on job description dataset
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.
Implementation of various Machine Learning and Deep Learning models for Sentiment Analysis on the 'Sentiment Labelled Sentences Data Set' by University of California, Irvine.
Arabic_Dialect_Identification_NLP-AIM-Task
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.
Fake news detection using TF-IDF vectorization and LinearSVC
In this project I intend to predict customer churn on bank data.
Erdos Institute Bootcamp project analyzing cuisines by recipe ingredient lists.
Scraping data through Instagram and using the data to build a predictive model
NLP Classification and Clustering with spam SMS dataset
This project was built within 24h by the team Augusteam for the DevHacks 2022 Climate Change hackathon sponsored by Systematic and it won the third place worth 500€
Implementation of Drug database with LinearSVC, BernoulliNB, MultinomialNB, LogisticRegression, Perceptron and MLPClassifier models
The aim is to create a classifier that indicates whether a requested transaction is genuine or fraudulent.
A mini ML project of feature and model selection on breast cancer data
Movie genre classification in NLP using multinomial navie bayes classification and linear support vector classification.
Dartmouth COSC 274: Machine Learning models for Amazon Reviews dataset
Fake news related to the coronavirus pandemic has now become a huge problem since false information can lead to worry and concerns regarding the disease. It is not possible to perfectly detect fake news unless the news has been labelled fake or real. Therefore, I have taken this issue as my problem and have developed a project that can detect fake news regarding Covid19 pandemic with the help of the dataset from Kaggle containing Covid19 public media information. I have also used different machine learning classifiers to check which classifier is best suited for the detection
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
Part of an internal project for my internship
In this part I'm working on Maternal Health Risk Prediction
The purpose of this project is to build a machine learning model to classify SMS messages as either "spam" or "ham" (not spam). Using TF-IDF vectorization and LinearSVC, it reads an SMS dataset, transforms text data into numerical features, and trains a model to distinguish between spam and ham. The "SMSSpamCollection" dataset has labeled messages.
DevStack Solution Internship Program "Data Science Internship" Task-1 on Fake news detecting system using python and machine learning
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.
Application of LSTM on imdb dataset for sentiment classification problem
A Breast Cancer Prediction Model
A flask app to prdict iris flower using LinearSVC deployed on heroku
This project aims to determine the likelihood of a company facing bankruptcy, a crucial aspect of financial analysis and investment decision-making.
The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 150.
Machine Learning clasificación con SKLearn