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The "Reality Check" application is designed to classify images of faces as either real or AI-generated. Utilizing the ResNet50 model, our classifier achieves up to 95% accuracy. This repository provides an overview of the application, detailed results from experiments, and future scope for enhancements.
This project aims to analyze and visualize the trends and insights related to diabetes. Using Power BI, various metrics and data points are visualized to understand the patterns, risk factors, and demographic details associated with diabetes.
This project focuses on analyzing a comprehensive dataset from a bike store, which includes information about customers, orders, products, stores, and staff. The analysis aims to uncover insights into customer behavior, sales performance, product trends, and staff efficiency.
Fruits Classification Using Transfer Learning
Diabetes Prediction
Repositories
14The "Reality Check" application is designed to classify images of faces as either real or AI-generated. Utilizing the ResNet50 model, our classifier achieves up to 95% accuracy. This repository provides an overview of the application, detailed results from experiments, and future scope for enhancements.
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This project aims to analyze and visualize the trends and insights related to diabetes. Using Power BI, various metrics and data points are visualized to understand the patterns, risk factors, and demographic details associated with diabetes.
This project focuses on analyzing a comprehensive dataset from a bike store, which includes information about customers, orders, products, stores, and staff. The analysis aims to uncover insights into customer behavior, sales performance, product trends, and staff efficiency.
Fruits Classification Using Transfer Learning
Diabetes Prediction
Flower Classification With Transfer Learning.
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The following notebook is the my first Kaggle competition notebook, in which I predicted the survival rate of the passengers travelling the titanic based on their Gender, Passenger Class, Age, Fare and Parch.
In this project, I have taken out the some insights of the Nobel prize like who got large number time Nobel Prize, which year Nobel Prize was not awarded? which country leads the least? etc
In this Project I'm have predicted the diabetes of a person whether he/she have daibetes or not using the Kaggle dataset. The three machine learning algorithm I'm have used are Logistic regression,Random Forest and XGBCalssifier. In the end I have also provided the compariosn between this different Machine Learning Models.