unsa4 Goto Github PK

about-me

apriori-algo-python

My first data mining algorithm implementation

credit-card-fraud-detection-task5-

This was my Task5 during my internship at Codsoft. i used random forests classifier with accuracy of 94% for fraud detection.

data-analysis-unsa

fashion-compatibilty

fashion_compatability

Used CNN and multi layered network in order to calculate the outfit compatabilty score as well as pair compatible clothing items in the dataset.

hibernate-app

A single entity application developed using hibernate that implements the concept of ORM in Java and the db i used is MySql.

iris-flower-classification-task3-

This was my Task3 during my internship at Codsoft. I Leveraged deep learning algorithms, including Neural Networks to create an accurate classification model. The activation function i used is sigmoid. The model achieved an impressive 90% accuracy on classifying iris flowers.

laundry-ms-

I developed this project using springboot as backend, netbeans for frontend and MongoDB as a no sql db.

loginsignup-

Login Signup Pages using Java Swing and MySql DB.

moving-rating-task2-

This was my Task 2 during my internship at Codsoft. I utilized state-of-the-art Decision Tree Classifier machine learning model for predictions. Achieved an impressive output {Mean Squared Error (MSE): 0.84 Mean absolute error: 0.6170794192997439 R2 score: 0.5464928722394091} on our predictions.

mvc-framework

My 2nd C# project using MVC framework

pygame-alien-invasion

My first project !

recipe-to-cuisine-classification

Used Logistic Regression and some model fine tuning techniques in order to achieve maximum accuracy.

rest-api-using-nodejs

This is my 5th semester project that i developed using HTML, CSS ,MONGO DB and Node JS.

sales-prediction-task4-

This was my Task4 during my internship at Codsoft. I used Random Forest Regressor to make accurate predictions.

shopping-cart

Using OOP (py)

titanic-survival-prediction-task1-

This was my Task1 during my internship at Codsoft in which i utilized a Random Forest Classifier with hyperparameter tuning to build a predictive model. Achieved an impressive accuracy rate of 100% on the predictions

web-api

This is my first Asp.Net project