Python hands on tutorial with 50+ Python Application (10 lines of code) By @xiaowuc2

This repository showcases a selection of machine learning projects undertaken to understand and master various ML concepts. Each project reflects commitment to applying theoretical knowledge to practical scenarios, demonstrating proficiency in machine learning techniques and tools.

Machine Learning projects with source code - Machine Learning projects for beginners, ML projects for final year college students, machine learning projects - beginner to advanced

🛣 Building an end-to-end Promptable Semantic Segmentation (Computer Vision) project from training to inferencing a model on LandCover.ai data (Satellite Imagery).

Repo for 42 days project to replicate/improve Airbnb's amenity (object) detection pipeline.

This application aims to early detection of lung cancer to give patients the best chance at recovery and survival using CNN Model.

This project focuses on predicting the prices of Bitcoins, the most in-demand cryptocurrency of today's world.

Android Malware Detection Using Machine Learning Project with Source Code and Documents Plus Video Explanation

Credit Card Fraud Detection Project with Code and Documents

Estimated annual CO2 emissions from diesel generators at mobile or cell towers

This project guides the user till they perform correct yoga pose.

Stock Forecasting System using AWS forecast.

📷 Generates Text Analytics using Bag of Words. Upload your data and it will suggest the relevant Newsgroups for you.

This repository contains my machine learning models implementation code using streamlit in the Python programming language.

This project aims to predict customer conversion for an insurance company. Using historical data, we will develop a machine learning model that can identify which customers are most likely to purchase a policy. By understanding the patterns and behaviors of previous customers, the model can make predictions and provide valuable insight to company.

Moving Object Detection with python using openCV

Pneumonia detection ML model

We solve a regression problem in which it consists of calculating the health insurance charge in the United States Where we will break down the project into 5 phases: Exploratory Analysis. Feature Engineering. Selection of the ideal model. Development of the final model. Creation of a web application in streamlit.

Detecting COVID-19 with Chest X-Ray using PyTorch from COVID-19 Radiography Dataset on Kaggle

This project is about creating a machine learning model that can predict the house value based on the given dataset. We use different machine learning algorithms such as linear regression, decision tree and random forest to train the model, and the model that gives the best performance is used to predict the house value for new data.

Car Price Prediction Project through Machine Learning Algorithm with Video Implementation

A machine learning-based UPI fraud detection system that analyzes transaction patterns to identify and flag suspicious activity. The project includes data preprocessing, model training, and a user-friendly web interface for real-time fraud prediction.

Fake News Detection using Machine Learning Algorithms and deploying using Flask

This project is a Streamlit-based interactive web application that allows users to explore 128 years of Olympic history (1896–2024) using data analysis and visualizations.

No description provided.

PGDBA - ML-miniproject - Telephone-Data-Churn

Machine Learning / Data mining project in python. In this project, various classification algorithms such as Decision Tree, k-nearest neighbours, random forest and support vector machine have been implemented from scratch and have been applied on banknote authentication dataset. The goal of this project is to calculate and compare the accuracy of these algorithms in differentiating counterfeit bank notes from legitimate notes

Machine learning project aimed at predicting diabetes using patient health data

This project focuses on detecting fraudulent payment transactions using machine learning techniques.

This is based on a data challenge from the Michigan Data Science Team (MDST). The Michigan Data Science Team (MDST) and the Michigan Student Symposium for Interdisciplinary Statistical Sciences (MSSISS) have partnered with the City of Detroit to help solve one of the most pressing problems facing Detroit - blight. Blight violations are issued by the city to individuals who allow their properties to remain in a deteriorated condition. Every year, the city of Detroit issues millions of dollars in fines to residents and every year, many of these fines remain unpaid. Enforcing unpaid blight fines is a costly and tedious process, so the city wants to know: how can we increase blight ticket compliance?