omarnahdi Goto Github PK

ats-system-gemini-vision-pro

🚀 Gemini Pro Vision ATS System: Revolutionize your job application process with our advanced Applicant Tracking System. Beyond traditional ATS capabilities, Gemini Pro Vision provides personalized feedback for resume enhancement using cutting-edge technology. Elevate your job prospects with precise analysis and tailored suggestions. 🌐

customer-segmentation

diabetes-prediction

🚀 Dive into the future of healthcare with my Diabetes Prediction ML Project! 🤖🩺 I've crafted a cutting-edge machine learning model that assesses the likelihood of diabetes, blending data science prowess with health insights. 📊💡 Empowering both healthcare professionals and individuals, my project aims to revolutionize diabetes risk

edible-mushrooms-ml-project

🍄 Mushroom Classifier Project 🌿 Dive into the fascinating world of mushrooms with my latest project! 🚀 Using Support Vector Machines (SVM) in machine learning, I've crafted a powerful model that predicts whether a mushroom is edible or poisonous based on its unique features.

google-stocks-prediction

📈💰 Predict stock prices with a linear regression model and 50DMA data 🚀 🎯 Make informed investment decisions 🧠💰 👩‍🏫👨‍🏫 Train a model and generate predictions 🔮 🤝 Contribute to the future of stock prediction 🚀

omarnahdi

Config files for my GitHub profile.

oneaistudio-sentiments-emotions-analyser

oneaistudio-text-generation-gpt-4-

sih-github-tut

testing

spam-detection-model

Spam Detection with Naive Bayes Algorithm 🚀 is an advanced tool using machine learning to efficiently identify and filter spam messages. With the Naive Bayes classification algorithm, customizable thresholds, and seamless integration, this project offers a reliable solution for real-time spam protection 🛡️.

titanic-survivors-prediciton

🚢 Titanic Survivor Prediction Model Predicting the likelihood of survival for Titanic passengers using a 🤖 machine learning model built with scikit-learn. The model is trained on a dataset featuring key attributes such as passenger class, gender, and age. Explore, use, and contribute to understand the factors influencing survival on the historic

webfirst