Jonathan-Monir

Attendance-System-Project

Attendance System Project based on Face Recognition Deployed with Streamlit

Credit_App

DSP-Tasks

Get_section_v2

This is a simple Streamlit app that allows students to quickly find their schedules for each section in their university. The app takes the student's name or seat number as input and returns a full timetable for his unique schedule appears in the app for him.

Heart-Disease-Prediction

Developed a predictive model to identify individuals at risk of heart disease using machine learning techniques. • Deployed the model using Streamlit.

House-Predection-Notebook

The house price prediction notebook, predicts the house price by analyzing factors such as size, date and condition using polynomial regression, then grouping prices into 3 categories using K-means.

Invo_app

Organize-folder

Creates dictionaries, add each file to the suitable place according to it's extension

Pumpkin_Seeds_Dataset

This project focuses on building a predictive model to identify the types of seeds based on 11 different attributes. The dataset was pre-processed and split into training and testing sets. The Support Vector Machine (SVM) algorithm was used along with hyperparameter tuning to improve the model's performance.

Water-Potability

1st place project in Machine Learning’22 summer training (ApplAI student activity-Ain Shams University)🥇

Jonathan-Monir/Get_section_v2

This is a simple Streamlit app that allows students to quickly find their schedules for each section in their university. The app takes the student's name or seat number as input and returns a full timetable for his unique schedule appears in the app for him.

Jonathan-Monir/Attendance-System-Project

Attendance System Project based on Face Recognition Deployed with Streamlit

Jonathan-Monir/Credit_App

Jonathan-Monir/DSP-Tasks

Jonathan-Monir/Heart-Disease-Prediction

Developed a predictive model to identify individuals at risk of heart disease using machine learning techniques. • Deployed the model using Streamlit.

Jonathan-Monir/House-Predection-Notebook

The house price prediction notebook, predicts the house price by analyzing factors such as size, date and condition using polynomial regression, then grouping prices into 3 categories using K-means.

Jonathan-Monir/Invo_app

Jonathan-Monir/Organize-folder

Creates dictionaries, add each file to the suitable place according to it's extension

Jonathan-Monir/Pumpkin_Seeds_Dataset

This project focuses on building a predictive model to identify the types of seeds based on 11 different attributes. The dataset was pre-processed and split into training and testing sets. The Support Vector Machine (SVM) algorithm was used along with hyperparameter tuning to improve the model's performance.

Jonathan-Monir/Water-Potability

1st place project in Machine Learning’22 summer training (ApplAI student activity-Ain Shams University)🥇

Jonathan-Monir/Pollution-Levels-Analysis

Jonathan-Monir/Text_Summarization