Deep learning, Machine learning, Statistics, Applied DS, Data visualization.
OOP Programming, Computer, and Software engineering.
Logitech • February 2019 - September 2019
- EDA and multivariate time series analysis of player rankings using PySpark and MLlib.
- Future player ranking forecasting using shallow learning models (linear models, SVM, Random Forest, Boosting Trees like XGBoost, LightGBM) and deep learning models implemented with Keras and Tensorflow.
- Acquired 0.9 R2 score using XGBoost on average by backtesting time series.
Logitech • August 2018 - February 2019
- Implementation of a demo file analyzer using Golang.
- 1.5 million data points collected by scraping several matchmaking servers using a self-implemented distributed web crawler created via Python (BS4) at the AWS (EC2, S3) platform.
- Data labeling by aggregating data points using the TrueSkill algorithm on Python.
- Preliminary exploratory data analysis, feature augmentation, and selection using Matplotlib, Seaborn, Plotly, Pandas, Pyspark, and Sklearn.
HAVELSAN • February 2017 - July 2017
Project : Hardware adaptor agent design and implementation using TCP-IP
- Software Integration of new hardware using adaptor agent coded in Java and C/C++. TCP - IP communication between the agent and the main system.
Project : Hardware input test tool, system and its UI design
- Implementation of a hardware test tool that validates the correctness of user input.
Python PySpark C/C++ Golang Tensorflow/Keras PyTorch SQL Tableau Web Scraping AWS Flask-RESTful Web Design Deep Learning Natural Language Processing Machine Learning Linux Pandas Sklearn Matplotlib
English — Professional Turkish — Native or Bilingual