yasin-peker

Debiasing-Facial-Recognition-Systems-MIT-DL-Lab2.2

This project is a part of MIT 6.S191 Introduction to Deep Learning course. In this lab, I build a facial detection model that learns the latent variables underlying face image datasets and uses this to adaptively re-sample the training data, thus mitigating any biases that may be present in order to train a debiased model.

HV-Transmission-Line-Selection

This project studies the selection of transmission lines according to the transmission line parameters such as number of circuits, number of bundle conductors and a library of ACSR conductors. There are different types of transmission towers, and each of these towers has different configurations.

Medical-Cost-Analysis-Project

A Machine Learning project trained by "Medical Cost Personal Datasets" from Kaggle and performance of different Regression models are compared.

Medical-X-Ray-Imaging

In this project, medical X-Ray imaging methods using MATLAB tools are studied. In order to design the model of the X-Ray imaging as software, the X-Ray imaging project is divided into two parts, namely the forward problem and the inverse problem

MNIST-Digit-Classification-MIT-DL-Lab2.1

This project is a part of MIT 6.S191 Introduction to Deep Learning course. In the first portion of this lab, we will build and train a convolutional neural network (CNN) for the classification of handwritten digits from the famous MNIST dataset. The MNIST dataset consists of 60,000 training images and 10,000 test images. Our classes are the digits 0-9.

Mushroom-Classification-Project

A Machine Learning project trained by the "Mushroom Classification" dataset from Kaggle.

Music_Generation_Project_MIT_DL_Lab1_2

This project is a part of MIT 6.S191 Introduction to Deep Learning course. In this project, I explored building a Recurrent Neural Network (RNN) for music generation. I trained a model to learn the patterns in raw sheet music in ABC notation and then use this model to generate new music.

Object-Detection-Using-YOLOv3

In this project, 4 different YOLOv3 models with different accuracy in different FPS values were created in the image processing area. The YOLOv3 models used are YOLOv3-tiny, YOLOv3-320, YOLOv3-416 and YOLOv3-618, respectively.

Signal-Transmission-Analog-vs-Digital-Transmission

In this notebook we will explore the potential advantages of digital transmission over analog transmission. We will consider the case of transmission over a long (e.g. transoceanic) cable in which several repeaters are used to compensate for the attenuation introduced by the transmission.

Training-Artificial-Neural-Network

In this project, I performed experiments on artificial neural network (ANN) training and drew conclusions from the experimental results. I implemented and trained multi layer perceptron (MLP) and convolutional neural network (CNN) classifiers on CIFAR-10 dataset.

Verilog-HDL-Based-Car-Parking-System-FPGA

This repository contains the Verilog HDL implementation of a Car Parking System running on an FPGA. The system is designed to manage car entry and exit through two sensors located at the entrance and exit of the car park. It allows registered users to enter the car park by entering their passwords and controls the traffic lights accordingly.

Verilog-Implementation-of-D-Flip-Flops

In this project, 8 distinct Verilog HDL implementations of D flip-flops (DFFs), encompassing rising and falling edge triggers, synchronous and asynchronous resets are designed.

darknet

Convolutional Neural Networks

Dogs-vs-Cats-Classification-Transfer-Learning

A Kaggle Dogs vs Cats dataset is used to train the pre-trained model, ResNet-50

Introduction-to-TensorFlow-MIT-DL-Lab1.1

This project is a part of MIT 6.S191 Introduction to Deep Learning course. In this Lab, I learned how computations are represented and how to define simple neural networks in TensorFlow.

skills-introduction-to-github

My clone repository

Walmart-Predictive-ML

The aim of this project is to build a predictive model and find the sales figures of each product at a particular store

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