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ZiyaddinovAsiman
I specialize in machine learning and data science, aiming to drive innovation in finance and business, with plans to advance my career in Silicon Valley.
경력
- Enhanced the service user interface by leading the UX/UI team, informed by user behavior analysis through Hotjar and Google Analytics. - Developed a comprehensive data collection strategy from the ground up and implemented it using Google Tag Manager. - Increased efficiency by 90% by automating the collection of POS data through web scraping, and created a recommendation system from scratch.
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- Conducted in-depth research on Object Detection and Instance Segmentation, thoroughly analyzing and replicating key works by prominent authors, including [Zhang et al. 2022], [Wang et al. 2022], [YOLOv5 2022], [Liu et al. 2021], [Wang et al. 2021], and [Hurtik et al. 2020]. - Developed a complete machine learning pipeline, along with data processing and visualization tools for data generation and analysis. - Achieved 90 mAP and 100 FPS (<10 ms) inference by creating lightweight models for detecting anomalies in noisy Railway and Catenary datasets. - Built software to flag incorrect model detections and allow users to provide feedback through the system. - Deployed the models using a TCP-based control software integrated into a PyQt Graphical User Interface (GUI).
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학력
I am a Computer Science major specializing in machine learning and data science, with a strong interest in applying these skills across both finance and business sectors. My goal is to work as a data scientist, leveraging data-driven insights to solve complex challenges and enhance decision-making processes. I am passionate about using innovative technologies to drive meaningful improvements in these industries while ultimately advancing my career in Silicon Valley.
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