mlproject

This project demonstrates the working of tensorflow-extended for creating scalable ML pipelines as well to automate CI/CD pipelines.

Detection of Skin Disease using CNN. Detects five types of disease.

Solving Sukodu puzzle in realtime using Deep Learning and Computer Vision. Display the unsolved Sudoku in front of the camera and get the instant solution projecting right on the image.

Facial Expression Recognition . Work on both Realtime as well as on a video .

The search is over. We present to you ‘Just Try It’’ where you can select any apparel,any accessory and put it on yourself to see how it looks! Decide after trying so you get only what you really want.

PGDBA - ML-miniproject - Telephone-Data-Churn

About Diabetic Retinopathy Detection: Utilizing Multiprocessing for Processing Large Datasets and Transfer Learning to Fine-Tune Deep Learning Models | PyTorch

Predicting & Classifying Brain tumor using CNN model

The project deals with the identification of high accuracy model among the given models to detect the cyberbullying in text by training them with the given dataset which is preprocessed and vectorized with tf-idf

Areca nut quality sorting is a manual process done by farmers, so this project is aimed to make areca nut quality sorting without human intervention

ML Project On Bank Churn Analysis Using ANN and Hyper-parameter tuning.

feasibility and practicality of using CNNs on a Raspberry Pi for on-site plant disease detection, providing farmers with an accessible and efficient tool to manage crop health effectively.

This repository contains a machine learning project focused on predicting gold prices (GLD) using historical stock market data, including indicators such as SPX, USO, SLV, and EUR/USD. The project implements a Random Forest Regressor for accurate price forecasting, complete with data visualization, correlation analysis, and model evaluation metrics

End-to-end ML project to predict customer churn with a deployed Streamlit app and actionable retention strategies.

Nutrify

Source code for Is this fake news! 🔥

🚢 Predict Titanic passenger survival using Machine Learning! This project trains a Logistic Regression model on the Titanic dataset and integrates it with a Streamlit web app for interactive predictions. Includes full code, datasets, and an easy-to-run app.

This contains the code of Bharat Book Collection(a dummy book store for project) Back-end.

Built a Machine Learning project to predict heart disease using patient health data. Includes data preprocessing, feature engineering, model training, evaluation, visualizations, and an interactive dashboard for predictions.