-comparative-analysis-of-artificial-neural-network-optimization-algorithms-on-cifar-10-with_pytorch

This GitHub project is designed to evaluate the experimental performance of various artificial neural network optimization algorithms using a multi-layer perceptron (MLP) classifier on the CIFAR-10 dataset.

blm19305e

Merve Çınar 1821221025

bookmanagment

it work like a library automation system

call-center_webapi_react

call-centerwebapp_mvc

Web Application with using ASP.net MVC and SqlServer

chess.lib

chessserverclient

health-insurance-premium-prediction-using-machine-learning

This project predicts health insurance premiums using machine learning. Accurate premium calculation is crucial for insurers and policyholders. Using data like age, sex, BMI, children, smoking status, and region, we apply Linear Regression, Decision Trees, and Random Forest models to forecast charges and analyze key factors.

iris-species

This is a app which calculate mean median variance boxplot histogram confide interval and other many thing I select Iris Species dataset and then speallength column I use swing jfreechart and database

lal.cpp

mervecinar

messenger_socketprogram

nlp_artificial_intelligence_recipe-recommendation-system

This project is a Flask web application that suggests recipes based on the user's emotional state. The application analyzes text input to determine the user's mood and provides recipes tailored to that mood.

ownshell

1821221025_MerveCinar

pathplaning-optimization-_gwo_aco_scso_woa

This repository presents a comprehensive comparison of four optimization algorithms applied to the path planning problem: Grey Wolf Optimization (GWO), Ant Colony Optimization (ACO), Sand Cat Swarm Optimization (SCSO), and Whale Optimization Algorithm (WOA)

philosopherdining

preprocesdecisiontreelogicregression

This code include steps of Data Mining Algorithms for Kaggle Dataset

productsfinderapp

This is help the find products using opencv.İt's works like a shopping Systems.

unet-semantic-segmentation-with-pytorch-on-cityscapes-dataset

This GitHub repository showcases my work on semantic segmentation using a Unet model with an encoder-decoder architecture, specifically tailored for the Cityscapes dataset. Semantic segmentation involves classifying each pixel in an image, and the Unet model is known for its effectiveness in this task.