Zeynep Özel

• Selected appropriate datasets and data representation methods.
• Managed infrastructure and data pipelines to bring codes to production.
• Designed machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
• Modeled predictions with feature selection algorithms.
• Researched and implemented best practices to improve existing machine learning infrastructure.
• Developed ML algorithms to analyze huge volumes of historical data to make predictions.

• Utilized advanced querying, visualization and analytics tools to analyze and process complex data sets.
• Carry out complex analyzes of customers database to optimize our customer knowledge (Segmentation, Scoring, Attrition model, etc.)
• Making results of these analyzes usable and communicate them to sales, marketing and management teams.
• Keeping abreast of modeling and data science methods.

• Assessed accuracy and effectiveness of new and existing data sources and data analysis techniques.
• Identified, measured and recommended improvement strategies for KPIs across business areas.
• Developed intricate algorithms based on deep-dive statistical analysis and predictive data modeling.
• Created and implemented new forecasting models to increase company productivity.
• Extracted and assessed data from databases to drive improvement of product development and business strategies and processes.
• Compiled, cleaned and manipulated data for proper handling.
• Modeled predictions with feature selection algorithms.
• Leveraged mathematical techniques to develop engineering and scientific solutions.
• Deep Learning, Kubernets, AWS Cloud, Google Cloud Platform(GCP), Docker, Python (Language Program), CVAT, Git, DVS, Anomalib,
  ModelOps ,Automated Pipeline(CD/CI), Pytorch, Tensorflow

Female mosquitoes lay their eggs in water, and after hatching mosquito larvae spend a week in this aquatic environment before they fly away as adults. The microbial and chemical composition of the water in which they spend their childhood affects the health of the larvae and the adult mosquitoes they will turn into. Previous research has shown that specific microbes or nutrients in the larval environment make for very healthy adult mosquitoes, whereas larval exposure to other compounds and bacterial strains decreases e.g the life-span of adult mosquitoes. It is unknown if/how female mosquitoes evaluate a body of water before she lays her precious eggs. In this project we aim to address this question, and hence determine if mosquitoes are good parents. Using computer vision (e.g. with raspberry pi cameras) you will track the movement of mosquitoes and figure out how they decide where to put their eggs. Hardware development will be done in the MakerLab, computer vision development in Python and OpenCV. Skills; annotation, object detection , segmentation, streamlit, Git and Github Model used; Resunet, Faster-RCNN, Mask-RCNN, Retinanet Experience with Pytorch, Detectron2, Tensorflow, Keras, OpenCV, TransferLearning,Augmentations, image preprossessing, Evaluation models, W&B tool for evaluation and result reports.

• Making interface and data scraping from the website and save in excel. Used Libraries: Scrapy, Selenium, Beautiful-soup, Pandas, PyQt5, Numpy, Urllib.request , Calendar, Os, Sys and more
• Creating API that cleaning, filtering data and extract from the web site by searching over the 2000 web page.
• And finally exporting data to excel all data with link and all needed information
• Design and testing od ADS systems Gaining knowledge and experience in the practical use of technology
• Conducted critical research into changing metrics causes and building a clear understanding of customers, user interactions and trends.
• Produced in-depth analyses and proposed solutions to meet complex business needs.
• Worked alongside team members and leaders to identify analytical requirements

• Created various Excel documents to assist with pulling metrics data and presenting information to stakeholders for concise explanations of best placement for needed resources.
• Produced monthly reports using advanced Excel spreadsheet functions.
• Identified, analyzed and interpreted trends or patterns in complex data sets.
• Worked with business intelligence software and various reports to glean insights into trends and prospects.
• Utilized data visualization tools to effectively communicate business insights.
• Synthesized complex analytics-derived insights into easy-to-understand, actionable recommendations for business users.
• Designed and developed data pipelines to acquire, clean and process data.