An approach to document exploration using Machine Learning. Let's cluster similar research articles together to make it easier for health professionals and researchers to find relevant research articles.

Final Year project based upon Network Intrusion Detection System

Contains code for a voting classifier that is part of an ensemble learning model for tweet classification (which includes an LSTM, a bayesian model and a proximity model) and a system for weighted voting

Recognition of Persomnality Types from Facebook status using Machine Learning

A model that could accurately predict the Industry Domain for different start-ups and companies based on descriptions, titles and categories.

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

Classifying Forest Cover type

This project presents Hera, an Operating System level voice recognition package that understands voice commands to perform actions to simplify the user’s workflow. We propose a modernistic way of interacting with Linux systems, where the latency of conventional physical inputs are minimized through the use of natural language speech recognition.

Classifying a website based on it's URL. I've implemented Stochastic Gradient Descent, Multinomial Naive Bayes and Convolutional Neural Network for classifying the category of the URL.

Recognize Handwritten Digits(persian/english) with Neural Networks

Sharing both theoretical and programing ideas, that I came across at Introduction to Machine Learning course. notes, homework solution and python assignment

Multiclass classification of Youtube videos using text mining.

Auto Classify Text

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

An automated tag prediction system on stackoverflow

In this notebook I've build a nlp/machine learning model that classify hotel-reviews.

Paid Promoters Recommender project objective is to make a recommendation system that recommends youtube content creators relevant to ads of advertisers.

Project made in Jupyter Notebook with "News Headlines Dataset For Sarcasm Detection" from Kaggle.

This project implements an NLP-based solution for filtering out e-mails as ham or spam.

This project detects AI-generated text using an ensemble of classifiers: Multinomial Naive Bayes, Logistic Regression, LightGBM, and CatBoost. It includes robust data preprocessing, model development, and evaluation, ensuring accurate identification of AI-generated content from a diverse text dataset.