This project creates machine learning models capable of classifying candidate exoplanets from the raw dataset from NASA Kepler Space Telescope

SMS/Email spam prediction machine learning model.

we will use supervised learning techniques to classify the independent component (IC) images of resting state functional magnetic resonance imaging (rs-fMRI) scans as Noise and Resting state network (RSN)

🔷 Diamond Price Prediction Model 🔷 - A machine learning project for accurately forecasting diamond prices. Explore data exploration, feature engineering, and model training, providing valuable insights into the diamond market."

Supervised ML - Regression Using Python This dataset was extracted and uploaded for the purpose of experimenting with and learning regression models for time prediction. There is also a lot of room for data cleaning, outliers in the data, and plenty of data to work with for more realistic model training, testing, and validation.

Implementation of Othello game with model training using evolutionary algorithms

A computer vision project using deep learning to detect face masks in live video. Accurate and efficient, it overlays results on the video feed, indicating mask presence. Monitors compliance in public spaces, workplaces, and healthcare settings for enhanced safety.

This project explores the predictive modeling workflow using the Kaggle competition "Titanic - Machine Learning from Disaster." It emphasizes key stages like data analysis and model evaluation, aiming to identify the optimal model. Through a real-world approach, we enhance our understanding of the workflow and emphasize rigorous model evaluation.

Predict loan defaults using ML. Leverage Logistic Regression, Random Forest, XGBoost. Preprocess data, train models, analyze features. Make informed lending decisions. Jupyter Notebook and code.

Contribution for Traffic Sign Detection and Warning System in real time with Custom Dataset & YOLOv8.

Revolutionizing Kidney Cancer Detection: Harnessing AI to Predict Renal Cell Carcinoma.

Collection of Jupyter notebooks and python code files explaining the essentials of Pytorch.

Predict Movie Ratings using Machine Learning, Regression

Successfully established a machine learning model which can predict an appropriate stellar class, on the basis of a distinct set of spectral characteristics, to a substantially high level of accuracy.

Implementation of digit recognition using the MNIST dataset. Train a model on grayscale handwritten digit images to accurately classify and predict numerical values of unseen digits.

Easy-to-Use library to recognize faces, train the model, provide predictions

This repository aims to create an end to end machine learning model using AWS Sagemaker.

Explore credit card approval prediction through data analysis and machine learning. Preprocess data, train logistic regression models, and optimize hyperparameters. Learn data preprocessing, feature engineering, model training, and evaluation. Dive into the world of machine learning with Python and popular libraries.

A learning rate range test implementation in PyTorch