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Candidate's Name , MSChicago,IL Street Address  661 5273 EMAIL AVAILABLE https://LINKEDIN LINK AVAILABLE EDUCATIONNortheastern Illinois University Chicago,ILComputer Science, GPA :3,Street Address  Master Degree Graduation Date: Dec 2023 Ankara Yildirim Beyazit University Ankara,TurkeyComputer Engineering, GPA: 3,17 Bachelor Degree Graduation Date: May 2021 WORK EXPERIENCELily and Fox Chicago,ILMachine Learning Engineer Jan 2023 - Jan 2024Developed and implemented machine learning algorithms such as Image Classification to optimize designed nail operations and improve decision-making processes for marketing which helps to detect and decide pricing. Conducted data analysis and model training to forecast trends and patterns in large datasets, resulting increase in revenue %5 for the first month.Collaborated with cross-functional teams to deploy machine learning models into production and ensured scalability and performance efficiency.Orchestrated the development of CNN models using TensorFlow and Keras, achieving a 32% boost in image processing speed and a 21% increase in accuracy. Implemented Airflow for workflow automation and Docker for environment consistency across development and production. Designed the data structure and annotation standard used to turn unstructured text into clean, user-friendly tables. Developed the first production deep learning model that extracted over 3 million customer characteristics using Pytorch and Python, helping customers filter over 1 million abstracts. Focused current with industry trends and advancements in machine learning to continuously improve and refine models, ensuring a competitive edge in the market. Created 5+ ETL pipeline (to train datasets) and 8+ ML pipelines with Pytorch, ski-kit-learn, and Numpy (training, assessing, and deploying models)Co-developed a chatbot using natural language that loweredcustomer service response time by 1.5 hours.Huel Group Chicago,ILMachine Learning Engineer Dec 2021 - Jan 2023Collaborated with cross-functional teams to identify data-driven solutions and improve operational efficiencies.Use machine learning and statistical modeling techniques to develop and evaluate algorithms to improve performance, quality, data management and accuracy.Developed and executed data analysis projects to identify trends, patterns, and insights for business strategy implementation.Created and maintained dashboards and reports using SQL and Tableau to communicate findings to key stakeholders Optimized algorithms and models to improve accuracy and performance, leading to a 20% reduction in error rate for a financial services firm.Developed and fine-tuned machine learning algorithms to accurately predict customer preferences for our products, resulting in a 20% increase in sales conversion rates. Implemented a comprehensive data validation process to ensure the accuracy of the ML algorithms, reducing error rates by 15% and improving prediction results by 30%. PROJECT EXPERIENCECNN Project Chicago,ILBrain tumor classification (MRI) Jan 2024 - Feb 2024 Experienced in addressing the challenges posed by brain tumors, which are recognized as aggressive diseases prevalent among both children and adults.Well-versed in statistical data regarding brain tumors, such as their contribution to 85 to 90 percent of all primary Central Nervous System (CNS) tumors.Competent in utilizing automated classification techniques leveraging Machine Learning (ML) and Artificial Intelligence (AI), particularly Deep Learning Algorithms such as Convolutional Neural Network (CNN), Artificial Neural Network (ANN), and Transfer Learning (TL).Proficient in proposing and implementing systems aimed at detection and classification of brain tumors, utilizing cutting-edge technologies to enhance accuracy and efficiency. Machine Learning Project Chicago,ILWhite & Black Sep 2021 - Dec 2021This is a Machine learning project and written wity Python, we leveraged advanced algorithms, including PCA, Nearest Neighbors, and K-Neighbors Classifier, to train our model using a dataset of colored images. We trained our model to convert colored images to black and white images, then we colorize the black and white images that we expect to have similar colors with this trained model. SKILLSComputer Vision and Machine Learning Models : Decision tree-based ML models: Random Forest, XGBoost- : Clustering methods: K-means, GMM (Gaussian Mixture Models), Mean-shift- : Regression models: Boosting algorithms, Linear Regression, SVR (Support Vector Regression) Machine Learning and Data Science Libraries : TensorFlow, PyTorch, Keras, OpenCV- : Jupyter Notebook- : Pandas, Scikit-learnVersion Control and CI/CD : Git, GitHubProgramming Languages : Java8,Java,Python,CData Management and Processing : SQL, MySQL- : NoSQL: MongoDBCONFERENCES-Web Page Information Extraction System by Using Deep Learning,4th International Conference on Computer Science and Engineering -Customer Clustering using RFM Analysis; 26th IEEE Signal Processing and Communications ApplicationsHONERS & AWARDSThe Most Highly Performed and Motivated Employee in the Computer Vision Projects of Lily and Fox, 2023 LINKSLinkedIn: https://LINKEDIN LINK AVAILABLE Github : https://github.com/Leventgmrkc