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梁賦康 （Foo-Hong, Leong） Taoyuan City, Taiwan Email: [email protected] Tel:Skills • Languages: Python • DataBases: MySQL, SQLite • Infrastructure tools: Github • Machine learning libraries: TensorFlow, Keras, and Scikit-learn • Data visualization tools: Power BI, Seaborn and Matplotlib • Deployment: Streamlit Summary I have been working in Motor Manufacturing Industry for 8 years. My first programming was going to my Bachelor's degree, C++ was the first program I learned. Then I started to learn Python in 2018 at TEDU and my first project was the Stock Trend Prediction by CNN. I kept

and a Bachelor’s degree in Electronic Engineering from the NKFUST. Proficient in firmware development using C, with hands-on experience in Embedded Linux System, MCU and Linux System, such as the OOB solution(on NUC980), Platform software Package, and FreeRTOS(on STM32) . comprehended to Python, TensorFlow, and machine learning concepts during university studies. Furthermore, I have proven track record of independently tackling challenging technical projects and embracing new technologies. I am passionate about continuous learning and self-improvement, as evidenced by my engagement in OOB solution, FreeRTOS, Yocto Linux kernel and machine learning with Python

工程師培訓 緯育TibaMe就業養成班 • Python程式開發 、 爬蟲程式設計與資料庫 • OpenCV影像數據與辨識 • AI LineBot 機器人應用 • AI 雲端部署實作 、 機器學習與深度學習 • Tableau資料視覺化 七月三月 2023 影片後製 韓商步鄰客股份有限公司 • 剪出數隻破百萬影片，其中最高為Facebook

Chin Ya Chang Machine Learning Engineer New Taipei City , Taiwan [email protected] Current Position: AI Team - Software Engineer at the Central Weather Bureau, specializing in machine learning. Tasks include image generation, numerical prediction, data calibration, recommendation systems, and text generation using data from satellites, radar, and geographic information. I stay updated on AI advancements by studying research papers and implementing new approaches into projects. Recently, I've focused on deploying Large Language Models (LLM) in customer-oriented chatbots. Proficient in Docker for establishing and maintaining development environments, deploying projects to client environments.

model to make the company’s private AI (Vector DB), or connecting to the API of public generative AI through prompt, or It uses golang and k8s api to create extensions, yaml or Terraform for automated deployment. 4. Use tensorflow's forests decision prediction to obtain some information, machine learning frameworks such as tensorflow and pytorch, and also use huggingface's lib to connect multiple models (self-study of basic AI or machine learning and other related knowledge), and also study google self attention model, etc. 5. Experience in using multiple clouds, and using Terrafrom to

相對應的數據分析 - 針對不同 project 進行 exploratory data analysis 分析 AI 工程師 • 林口長庚醫院-AI core lab 六月三月 2021 【建置 AI 模型與應用】 - 利用 AI deep learning CNN models，解決醫療領域的問題 - 利用機器學習方法輔助解決醫療領域問題 - 搭配 Linux bash shell 幫助 AI 模型的運行 1. Corneal ulcer - 建立 two

fraudulent accounts based on transaction data, restricting transactions in advance to prevent harm. Responsibilities/Achievements: Development and deployment of credit card and financial features. Managing the data flow process from receiving variables to model predictions, identifying risk factors, and updating alert lists. Implemented Autoencoder + contrastive learning to achieve a 1.81% improvement in model effectiveness. Coupon Recommendation Objective: Personalized coupon recommendations for mobile banking users to increase click-through rates and redemption rates. Responsibilities/Achievements: Utilized multi-task learning to simultaneously predict click-through behavior and coupon redemptions, resulting in a