goksuturac
Göksu Turaç

Hi I'm Göksu Turaç

I have recently graduated from Eskişehir Technical University with a degree in Computer Engineering. Additionally, I have completed a minor program in Artificial Intelligence and Machine Learning at Eskişehir Technical University. During my studies, I was a lab student at the AI in Healthcare Lab, where I focused on developing my skills in image processing and machine learning.

I am currently seeking a position in the field of artificial intelligence and machine learning.

python tensorflow pytorch keras opencv yolo matplotlib scikitlearn pandas numpy vscode python tensorflow pytorch keras opencv yolo matplotlib scikitlearn pandas numpy vscode python tensorflow pytorch keras opencv yolo matplotlib scikitlearn pandas numpy vscode python tensorflow pytorch keras opencv yolo matplotlib scikitlearn pandas numpy vscode

About Me Education

Eskisehir Technical University

Master of Science in Computer Engineering

Sep. 2024 – Current

Eskisehir, Türkiye

Eskisehir Technical University

Minor in Artificial Intelligence and Machine Learning

Feb. 2021 – Jan. 2024

Eskisehir, Türkiye

Eskisehir Technical University

Bachelor of Science in Computer Engineering

Sep. 2019 – Jun. 2024

Eskisehir, Türkiye

About Me Skills

Languages

  • Python
  • SQL
  • Java

Python Libraries

  • Scikit-learn
  • OpenCV
  • Tensorflow
  • Keras
  • PyTorch
  • os
  • PIL
  • Gradio
  • Numpy
  • Pandas
  • Matplotlib
  • Seaborn

A bit about me

I have worked on data analysis, model development, and algorithm design using Python. I have carried out projects particularly in the fields of machine learning algorithms, deep learning algorithms and computer vision. My projects span across various domains such as healthcare, finance, and commerce. I have experience working with large datasets, performing data cleaning, transformation, and feature engineering. I have also applied augmentation techniques to balance imbalanced datasets. I am proficient in using popular libraries such as TensorFlow, Keras, and PyTorch for modeling. Additionally, I have experience in model evaluation, hyperparameter optimization, and utilizing explainable AI (XAI) methods to enhance the accuracy and reliability of projects. Furthermore, I have developed end-to-end projects by integrating models into user interfaces using the Gradio library.

Recent Work Experience

Workplace 1 - YouTube Creator
AI in Healthcare Lab

AI in Healthcare Lab

Lab Student
Sep 2023 – Jun 2024

The thesis project was developed here.

Theoretical and practical experience was gained in machine learning and image analysis.

Visea
Visea Innovative

Visea Innovative

CV and ML Intern
Feb 2024 – Apr 2024

Image processing techniques were utilized in the projects.

The VGG16 model within PyTorch was utilized in the Emotion Recognition project.

Object detection was conducted using YOLOv7 and YOLOv8 algorithms.

Segmentation performed using U-Net architecture with ResNet.

Drupart
Drupart R&D

Drupart R&D

Software Engineering Intern
Jul 2023 – Jul 2023

In the project, the UI/UX design part was done using Figma.

The web page, designed in Figma, was coded with adherence to SEO rules and utilizing Bootstrap 5.3.

Git was employed for source code review, code sharing, branching structure, and version control management.

Project Thesis Project

Eye Disease Detection, Severity Prediction, Localization with Focal Loss and Grad-CAM

The system has three main components: (i) The eye disease prediction model is trained with a dataset containing fundus images with six different diseases. (ii) The diabetic retinopathy severity prediction model is trained with fundus images obtained from patients with diabetic retinopathy labeled with the stage of the disease. (iii) The system locates the regions related to eye diseases using the Grad-CAM.

Models Used

MobileNet
ResNet50
InceptionV3
VGG16

Libraries Used

Tensorflow
Keras
PIL
os
OpenCV
Pandas
NumPy
Sklearn
Matplotlib
Seaborn
Gradio

🏆 The project has been selected as the winner among 31 groups at the 17th Project Fair and Competition held at Eskisehir Technical University on May 28, 2024.

🎓 This research was presented at the Engineering Sciences and Research Student Congress, Ankara, Atilim University, 2024.