The Pneumonia Detection App is a web application designed to assist in the diagnosis of pneumonia using chest X-ray images. This project utilizes deep learning techniques implemented with TensorFlow and Keras for image classification, and is deployed using Streamlit for a user-friendly interface.

a library so simple you will learn Within An Hour

Taxi Fare predictor using Random Forest and GridSearchCV for Hyperparameter Tuning

Multi-class classification model to predict outcomes of cirrhosis patients using machine learning

Successfully fine-tuned a pretrained DistilBERT transformer model that can classify social media text data into one of 4 cyberbullying labels i.e. ethnicity/race, gender/sexual, religion and not cyberbullying with a remarkable accuracy of 99%.

Heart failure is a severe condition in which the heart is unable to pump blood effectively. Early prediction of heart failure can significantly improve patient outcomes. This project aims to build a predictive model using machine learning techniques to identify patients at risk of heart failure.

This project provides a comprehensive guide to implementing PCA from scratch and validating it using scikit-learn's implementation. The visualizations help in understanding the data's variance and the effectiveness of dimensionality reduction.

this computer vision / machine learning project uses YOLO to detect players, referees, and the ball, k-means for pixel segmentation (and to group players by their teams), and optical flow for motion tracking.

Leveraging data-driven approaches to mitigate Credit Risk and optimize financial strategies in the banking sector.

The purpose of this project is to predict student loan repayment success using a neural network. Neural networks are computational models inspired by the human brain's structure and function, consisting of layers of interconnected nodes or "neurons" that can learn to recognize patterns in data.

An Image classifier model and builder for binary image classification.

This is my public repository with mostly experimental code I write while exploring or creating various deep(or not so deep) neural networks.

This repository contains code for predicting house sales prices using machine learning models. It includes data preprocessing, model training, evaluation, and prediction on test data.

Simple ML system for the iris problem

Successfully established a Seq2Seq with attention model which can perform English to Spanish language translation up to an accuracy of almost 97%.

Successfully developed a fine-tuned DistilBERT transformer model which can accurately predict the overall sentiment of a piece of financial news up to an accuracy of nearly 81.5%.

Successfully developed a fine-tuned BERT transformer model which can accurately classify symptoms to their corresponding diseases upto an accuracy of 89%.

University Admission Predictor is a sophisticated Flask-based web application designed to predict the likelihood of admission to graduate programs based on student profiles. It leverages a range of regression techniques to evaluate admission chances.This project showcases the practical application of machine learning in educational forecasting.

Extensive Collection of Jupyter Notebooks focused on Machine Learning covering different techniques includes Feature Engineering, Feature Selection, Feature Extraction, Model Training & Testing.

Comment classifier model trainer using keras tensorflow, stanza tokenizer and transformers.