Stock Market Predictor for Optimal Investment with a Timeframe to Maximize Model Accuracy (On going)

Hierarchical Tree-structured Knowledge Graph For Academic Insight Survey (INISTA 2024)

One click guide to create token on Eclipse Mainnet Beta or on Eclipse Testnet

Machine Learning Algorithms & Data Manipulation with Python A collection of machine learning algorithms and data manipulation techniques using Python and Scikit-learn. Covers regression, classification, clustering, and neural networks, using real email and NSL-KDD datasets for practical applications.

Have you ever tried to guess the genre of a book by reading its title? Well, in this project, I was trying to do it using a massive database of Books (their titles and genres), MLLib Spark, and the use of three different ML models, including: 1- Support Vector Machine (SVM) 2- Logistic Regression 3- Neural Networks

Heart disease predicting model in Web Interface.

NLP based Industrial Accident Severity Assessment

Project based on SVM and Random Forest to detect Intrusion on network traffic

Sign Language Detection & Translation Web App

A website visualising various classification algorithms

Investigate personnel elements influencing organizational dynamics by looking at HR analytics data using python and advanced machine learning models. Forecast employment status, estimate the period of termination, and maximize performance and satisfaction initiatives.

Own implementation of SVM classifier solving dual optimization problem

Digit Recognizer, is a web-based tool designed to recognize handwritten digits using machine learning techniques. With the advancement of deep learning and image recognition algorithms, it has become feasible to build accurate models capable of identifying handwritten digits with high precision.

Project for the Machine Learning 2021/22 class at the Faculty of Economic Sciences, University of Warsaw. I was responsible for the drug abuse prediction task for which I build logit, probit, KNN and SVM classification models.

Visualizes the data, builds a multi-linear regression model, applies a 10-fold cross-validation resampling method, and evaluates LM, SVM, and KNN model performance using R

Iris Classification : Developed a ML Model for classifying iris flowers based on their features using Python, scikit-learn, and TensorFlow.

This repository contains my code for predicting whether or not a passenger on the Titanic survived using SVM.