Cagla Nur Oksuz

Phone: 737-***-**** Github.com/Cagla-oksuz Email: adpkhk@r.postjobfree.com Linkedin.com/in/cagla-nur-oksuz Highly motivated and detail-orented Software engineer with Bachelor degree in Computer science seeking the next advancement of my career. Professional in analyzing real-world problems, developing algorithm and coding necessary models and formulas, and creating the desired reports graphically from the results. Having expetrise knowledge in Model.fit (data), Application of Computer Vision including Image Processing, Optimization, TensorFlow, Python, OpenCV, NumPy, Keras, TFLearn, PIL, Matplotlib, DNN, CNN, R-CNN, Fast R-CNN, Fuzzy logic, SQL, Decision trees and gradient boosting machine learning algorithms Academic Background

Sakarya University (Turkey) - Bachelor’s Degree in Computer Sciences - Software Engineer Sep 2016 – Jun 2020

- Graduated with honor

- Was on the board of the Free Software Community in college. 2016-2017

- Took part in the robot design project in the innovation community. 2017-2019

- Has voluntarily taught blind students with the Togev Society. 2018-2020 Experience

Software Developer - BBS Company (Internship) Jun 2019 – Dec 2019 Worked with Multi-Layered Architecture and product tracking system, by applying C#, SQL and where HTML was used. Gained experience with the Engineering group's best practices, coding standards, policies and procedures

- Developed and executed unit tests and delivered front end applications

- Collaborated with colleagues locally and in remote locations

- Provided service to MS Corporation’s, HP, Lenovo, etc. for their cooperation in Turkey Hardware Developer - BBS Company (Internship) Jan 2019 – Jun 2019 Incubated new products, technologies, and features that enable product innovation. Conducted computer diagnostics, as part of a solution installation of Windows system in limited period of time.

- Developed and executed unit tests and delivered front end applications

- Designed new computer hardware, and created blueprints of computer equipment to be built.

- Provided service to MS Corporation’s, HP, Lenovo, etc. for their cooperation in Turkey Projects Involved

Bachelor Degree - Graduation Thesis Project Oct 2019 – Jun 2020 The project’s focus was to develop a new object detection and counting techniques and model in retail business. Used the test data and the model's predictions, mathematical equations and the necessary graphics were created and interpreted by applying Python, TensorFlow API, Fast R-CNN, RPN, ROI Pooling, Label Map, Frozen Model, Eval.

- Algorithms applied: Fast R-CNN was used to make changes to th boxing function in TensorFlow API to control the object counting process. CSV format data file used for object counting. Actual object counts were thrown into the array. The object numbers predicted by the test results model were thrown into other arrays. Then, with the help of these sequences, the model accuracy was mathematically calculated.

- Machine Learning: A training of 2000 epochs has been carried out. Frozen model was used for the test and several proofs were made.It was concluded that the object detection and counting model worked and proofed the equation for all 4 objectswith overall success rate of 83%. High accuracy of this model offered to be a new faster solution in many industries including retail businesses.

Object Detection with Tensorflow Sep 2019 – Dec 2019 Project was continuation of object detection with TensorFlow and the main objective of the project was to distinguish specific objects by applying TensorFlow, TFLearn, PIL, Numpy, OpenCv, Matplotlib.

- 7-layer CNN consisting of 5 convolutional layers were used. The average pixel of the images with different pixel values was calculated. Image processing was used.

- With this pixel value, each image is adjusted to be 375x375 with the PIL library.

- Arrangements were made on the images, and they were made available for use on the model.

- As a result of the project val_acc: 0.0033 decreased to val_loss:0.95.

- The accuracy rate of 87% was proven with the test data. C#(Visual-Studio): Anti-Aircraft Game (console application) CSS/JavaScript: Disease survey application with react native Java (NetBeans): Apply fuzzy logic with blood data set;

- A fuzzy model is created, member function, blurring, rinsing data interpretation is done.

- Mean Absolute Percentage Error calculation done.

- The ability of people to donate blood was examined by applying YSA with the blood data set. Python (Anaconda): 6 different classes of Cifar 100 dataset were used.

- The model, which was created and tested with the Keras library retrained by dropout and image generation.

- Results compared with graphs.

- An application has been developed to add emblems on the image.

- Another project; To save time by placing the same or different emblems on a large amount of images in one phase. Technical Skills

- Software Languages: Python, Java, C#, C/C++, JavaScript, CSS, SQL, PostgreSQL, Git, Linux Server, Object Oriented Design, Big Data, Anaconda Navitagor, Visual Studio, NetBeans, React Native.

- ML: Document Classification, Information Retrieval, Clustering, Grid Search, Model Selection, Neural Networks, CNN, RCNN, Fast R-CNN, YOLO, MAPE.

- Skills: Python, Java, C#, C/C++, JavaScript, CSS, HTML, Object-Oriented Programming, Classification, Computer Vision, CNN, R-CNN, Fast R-CNN, Machine Learning, Data Science, Algorithms, Image Processing, Data Structures, Optimization Algorithms, SQL, Anaconda Navigator, Visual Studio, NetBeans, Jupyter, Linux, MacOS, Windows.