androidlearningapp

This is android learning(Preparation and quiz)app

animation

Animation app for different types of animation

basic-mvc-application

This is a basic MVC application that save student record

bee-species-image-classification

This project focuses on using the Python image library Pillow to load and manipulate image data, perform common image transformations, and build them into a data processing pipeline.

blood-donation-app-using-real-time-database

Simple blood donation app with add operation using realtime database in firebase

book-shop-application-using-asp.net

This is MVC Asp.Net application that uses database first approach and use sql database to save records

calculator

Simple Calculator app

calculatorform

car_price_prediction

Trains Random Forest and Gradient Boosting models to predict car prices based on user inputs for various car attributes, evaluating models and making predictions using the best-performing model.

certificates

This is my repository showcasing my professional development journey through various courses and achievements.

customerapplication-sql-server

This is a simple customer application that uses sql server to perform all crud applications

customerapplicationusing-oop-concepts

This is a simple customer application that uses SQL server and also uses OOP concept for secure software development and performs all CRUD operations.

cv_maker

This is a CV maker app with taking data from user and make CV for user

data-wrangling

This is a basic step of data analysis that is data wrangling or data cleaning

databaseandlist

This is a simple project that uses list view to save data and also do other operations on list view also it add data to database

databinding-in-wpf

This is a simple WPF application that uses element and data binding

diabetes-prediction-project-using-random-forest

This project focuses on predicting the likelihood of a person having diabetes based on various health-related attributes using Random Forest Algorithm

diabetes-prediction-project-using-voting-classifier

This project focuses on predicting the likelihood of a person having diabetes based on various health-related attributes. It employs a Voting Classifier, which combines the predictions of multiple machine learning models, to improve prediction accuracy.

diabetes-prediction-web-app

This repository contains the code for a web-based diabetes prediction application using a machine learning model. The application is built using Flask and allows users to input various health parameters to predict the likelihood of diabetes using ensemble voting classifier.

diabetesprediction

This is a diabetes prediction system using Random Forest classifier and Flask framework.

digital_tasbeeh

This is digital Tasbeeh android app that counts the tasbeeh

eartquake_magnitude_prediction

This repository contains a Flask web application that uses a CatBoost regression model to predict earthquake magnitudes. The model is trained using a dataset containing various features related to earthquakes.

email_spam_classification

This code performs email spam classification using three machine learning models: Naive Bayes, Support Vector Machines (SVM), and Random Forest Classifier. It evaluates their performance using accuracy scores and classification reports, ultimately identifying Random Forest Classifier as the best performer among the three.

exploratory-data-analysis

This is a important step in data analysis ,this is a simple code for some important parts of exploratory data analysis.

fatimaafzaal

Config files for my GitHub profile.

firebase-authentication

Simple Authentication using firebase

first-datascience-basic-project

This is my first data science project that I have done on Data camp.

fruit-mart

guess-random-number-game

It is a simple but interesting Python program that ask user to enter number range and within that range it creates a random number and then ask user to guess number that is generated

hyperparameter_tuning_of_model

This code performs hyperparameter tuning using Grid Search and Random Search for a Random Forest Classifier on an email dataset, followed by evaluating the best models based on accuracy and classification reports.