This repository contains code and documentation for participating in the Kaggle competition: Used Car Price Prediction. The goal of the competition is to predict the price of used cars based on various attributes using machine learning models. The project is scored based on the Root Mean Squared Error (RMSE).

This repository contains an email spam detection system built using logistic regression, achieving an accuracy of 98%. The model was trained on a comprehensive dataset of labeled emails to effectively classify spam and non-spam messages.

Predictive Health Analytics for Diabetic Risk Assessment and Personalized Reporting WebApp using Streamlit

Developed a cutting-edge deep learning model to accurately analyze knee osteoarthritis from X-ray images. Leveraged convolutional neural networks (CNN) to enhance diagnostic precision, aiding in early detection and effective treatment planning. This project showcases my expertise in medical image analysis and advanced neural network architectures.

This project contains examples of Linear, Polynomial, and Logistic Regression models implemented using Python. Explore how different regression techniques can be applied to various datasets 🤖

A repository featurin BeautifulSoup for effective web scraping, enabling data extraction from diverse websites with practical examples and guides.

SoK: All You Need to Know About On-Device ML Model Extraction - The Gap Between Research and Practice

MIST Machine Leaning in Cybersecurity Workshop Code Dump Repository

This machine learning project predicts house prices based on diverse features, utilizing a dataset containing historical housing data. With organized directories for data, source code, and models, it provides a foundation for accurate predictions and future enhancements. 🏡📈

Gesture recognition library for Python

A notebook to learn the use of CNNs and ShuffleNet

Joint Deep Neural Networks for Simultaneous Object and Depth Detection

Resolución del desafío de la clase cuatro, última clase de la serie Inmersión de Datos de AluraLatam

This repo contains different models and technique used to classify image in MNIST, CIFSR-10, IRIS Datasets.

This project is about recognizing handwritten digits using custom architecture of Convolutional Neural Networks (CNN). The CNNs have been trained on a dataset of 1.5 million images, resulting in an impressive accuracy of 99.625% on Kaggle.

ML_binary classification application, docker image created by circleci_deployed to Heroku container

This is a machine learning minor project for predicting heart stroke using the classification technique. The ML model correctly predicts a heart stroke with 95% accuracy.

numpy resources

Template alur kerja machine learning.