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潘揚燊
智慧製造全端開發工程師 @聯華電子股份有限公司
・
2022 ~ Present
AI工程師、機器學習工程師、深度學習工程師、影像演算法工程師、資料科學家、Ai Application Engineer,Machine Learning Engineer,Deep Learning Engineer,Data Scientist
Within one month
員正確使用機器及降低故障率。 生產設備數據分析，製程問題進行分析，檢視錯誤原因，如: 負擔過重、溫度過高等。 Skills Python Langchain Numpy OpenCV Tensorflow (tf.keras) Pytorch Scikit-learn C# EmguCV ASP.NET Windows Forms 程式設計開發、單元測試專案 Halcon 影像處理 影像定位 瑕疵判斷 物件量測 Skills Database MySQL Oracle ArangoDB LLM
Python
Qt
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Employed
・
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元智大學 Yuan Ze University
・
工業工程與管理學系所
Avatar of 宋浩茹 Ellie Sung.
Avatar of 宋浩茹 Ellie Sung.
宋浩茹 Ellie Sung
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AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
Within one month
宋浩茹 Hao-Ru Sung| [email protected] | LinkedIn ｜ GitHub A s a Research Assistant at Academia Sinica , specializing in Generative AI research and application. With 3 + years of experience in NLP a nd Machine Learning , along with 4+ years in Backend Development . Proficient at translating complex theories into practical applications. Skills Languages: Python, R, SQL, MATLAB, C, C#, JavaScript, Node.js Software & Tools: PyTorch, PyTorch Lightning, Tensorflow, Scikit-Learn, NLTK , GCP, Linux, SQL / NoSQ , Pandas, Hugging Face, Gradio, LangChain, Tensorflow, Keras, FastAPI, OpenCV, Airflow
Python
R
Natural Language Processing (NLP)
Employed
・
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4-6 years
國立政治大學（National Chengchi University）
・
資訊科學系
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Product Manager @東元電機股份有限公司 (TECO Electric & Machinery Co. Ltd.)
・
2023 ~ 2023
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Within one month
Python
Power BI
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6-10 years
國立成功大學 National Cheng Kung University
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Mechanical Engineering
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Senior Firmware Engineer @Artesyn Embedded Technologies
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2019 ~ 2022
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Within one month
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日本電氣通信大學 The University of Electro-Communications (UEC)
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Robotics Engineering
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2021 ~ Present
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University of Qom
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Information Technology | Face Recognition
Avatar of Alex Yu.
Avatar of Alex Yu.
Alex Yu
Product Manager @Linker Vision
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2023 ~ Present
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detection, segmentation, and classification AI scenario. Good communication skills with doctors' demands and collaboration with colleagues. Patent Disclosure: Ultrasound detect and notify system. (serial number: I學歷 SepJun 2 National Taiwan University of Science and Technology Masters in Electrical Engineering Thesis "Online Data Stream Analytics for Dynamic Environments Using Self-Regularized Learning Framework", IEEE journal SepJun 2020 Yuan Ze University Bachelor in Electrical Engineering Skills Customer/VC negotiation and customer services DL/ML/AI algorithm, keen problem solving 3D modeling (Blender) Python, Matlab, Tensorflow, Keras Object detection, Classification, [email protected]
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4-6 years
國立台灣科技大學 National Taiwan University of Science and Technology
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電機工程
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Avatar of Kao Yu Chun.
Kao Yu Chun
Past
Full Stack Developer @PD Case Informática Ltda
・
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高鈺鈞 我有超過5年軟體開發經驗的開發者，專注於前端開發。在我的職業生涯中，我有機會接觸到多種編程語言，如Java（包括Android開發），JavaScript，Kotlin，TypeScript和Python；同時也涉及到多種技術和框架，包括Angular，React，Redux，Spring Boot，TensorFlow，Keras和OpenCV；還有Oracle，MySQL和ElasticSearch等資料庫技術。 我喜歡迎接
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docker
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巴西聯邦大學
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Avatar of 陳松頡/Center.
陳松頡/Center
高級軟體工程師 @瀚宇彩晶股份有限公司
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接受 https://ieeexplore.ieee.org/abstract/document/技能 / Skills 前端與框架 Html (Vue) CSS ( Bootstrap ) JavaScript C# 後端與框架 NodeJS (Express) Python(FastAPI / Flask) PHP(Laravel) C++ AI 框架 Tensorflow Keras Pytorch Onnx TensorRT OpenVINO 其他 Halcon VIDI Google Cloud Plateform AWS Document360 瑕疵檢測 網路爬蟲 工作經驗 / Work Experience 高級軟體工程師 瀚宇彩晶股份有限公司 2022/08
Python
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國立臺中科技大學National Taichung University of Science and Technology.
・
資訊工程系-碩士
Avatar of 林昭源 (Leo Lin).
Avatar of 林昭源 (Leo Lin).
林昭源 (Leo Lin)
資深經理 @緯創資通
・
2021 ~ Present
Technical Manager
Within six months
林昭源 (Leo Lin) 1. Two years of management experience. 2. More than 10 years of computer vision and deep learning/software architecture development experience. 3. Programming experience using python. 4. Good paper reading ability and practical ability 5. Familiar with computer vision, deep learning (CNN, Resnet, densnet, GAN), object detection (Yolo series, RCNN series), segmentation models (UNet, DensUNet). 6. Experience in semi-supervised or unsupervised learning (pesudo labeling, Voxmorph model). 7. Experience with Docker, Git, Jenkins DevOps. Education: National Taiwan University of Science and
Research
Unsupervised Learning
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10-15 years
National Taiwan University of Science and Technology
・
Master's degree Computer Science and Information Engineering
Avatar of 歐文.
Avatar of 歐文.
歐文
Past
資深軟體工程師 [產品研發部] @龎帝數位資訊有限公司
・
2018 ~ Present
Back-End, DevOps engineer
Within six months
歐文 Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna aliquam erat volutpat. Ut wisi enim ad minim veniam, quis nostrud exerci tation ullamcorper suscipit lobortis nisl ut aliquip ex ea commodo consequat. 工作經歷 資深工程師 • 龎帝數位資訊有限公司 MayMar 2023 軟體工程師，負責 DevOps 和 ML & MLOps 相關工作。 [DevOps] * 維護及開發基於 Django 的後端程式，包括 RESTful API 產
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淡江大學（Tamkang University）
・
資訊工程

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Avatar of 陳得翊.
陳得翊
國立交通大學
・
2020 ~ 2020
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Data Scientist
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國立交通大學
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統計學研究所
Print

陳得翊 William

Data analyst, Machine learning engineer

我是一個熱愛挖掘潛在問題的統計人，以客觀的角度分析問題及處理，重視團隊合作，開放的態度分享彼此不同的想法和意見，有效率的解決問題。就學期間致力研究於機器學習，降維(Dimension Reduction)以及模型分類問題。並與台北榮民總醫院合作結合人工智慧開發全方位疾病診斷，在臨床上預測病人在一年內是否發生中風，以及是否由肺靜脈引起心房顫動的3D影像分類。

  

Mobile: +886-988-313-160

Email: [email protected]

技能

Python

  • 視覺化：Matplotlib, Seaborn


  • 機器學習套件：
    Tensorflow, Keras, Scikit-learn, Fast.ai, OpenCV

Machine Learning

  • 模型：Random Forest, XGBoost, LightGBM, SVM, CNN, RNN, LSTM, ResNet
  • 特徵選擇：Genetic algorithm, Simulated Annealing

Dimension Reduction

Multidimensional Scaling (MDS), SCMDS, Principal component analysis (PCA), Factor analysis model, Lasso regression

學歷

2018 - 2020

國立交通大學

統計學研究所

論文題目：Using Machine Learning Model and Ensemble Learning to Predict Ischemic stroke

第三屆統計研究成果研討會海報論文競賽—特優獎


2014 - 2018

私立淡江大學

統計學係

相關課程：回歸分析, 類別資料分析, 實驗設計, 無母數統計, 多變量分析, 時間序列, 倖存分析

程式：R, SAS (SAS Certified Base Programmer)

社團：統計系籃球隊-隊長                                           大統盃,亞軍, 2016 大統盃季軍, 2017

專案經驗

國立交通大學與台北榮民總醫院心臟科

預測病人在一年內是否發生中風Ischemic Stroke

                                                                

透過機器學習 (Machine Learning) 預測病人在一年內是否發生腦缺血型中風 (Ischemic stroke) 並且提升模型在 auc 上的表現。研究過程我們遇到資料極度不平衡的問題，透過變數選擇 (Feature Selection) 幫助我們挑選重要的特徵，使用集成學習 (Ensemble Learning)及下採樣 (Under-sampling)結合多個模型及處理資料不平衡的問題。

國立交通大學

Modeling High-dimensional time series by Structural factor model

                      

研究威爾夏5000指數 (Wilshire 5000 index) 成分股，透過主成份分析 (Principle Component Analysis) by Bai and Ng, Ratio-based method by Lam and Yao, and Structural factor model by Gao and Tsai, 找出背後影響5000支股票的潛在變數。對應於潛在變數與5000支股票的權重，得到新的一組投資組合，比較投組與指數的報酬。 


國立交通大學與台北榮民總醫院心臟科

CT Images Classification of PV and Non-PV trigger by 3D Convolution Network

                                                                                                

一位病人通常會有多張CT影像，有些影像包含疾病而有些影像則未包含， 使用3D CNN 可以使模型以病人為單位而非影像。在3D影像前處理對於像素的長寬和影像之間的切片厚度做歸一化。由於每位病人的影像張數不同， 在張數較少的病人上下補上黑色影像。在模型的選擇上使用 3D Resnet 做 模型訓練，針對資料不平衡的問題，我們對病人的影像做旋轉使得少數類 病人與多數類病人以相同比例進入模型。                                                              


Kaggle

Predict Future Sales (Top 8%)

                                                                                                

資料集由俄羅斯1C公司提供，紀錄2013/01~2015/10的日資料，目的是預測下個月每個產品和商店的總銷售額。在EDA探討各變數與總銷售額的marginal effect，以及變數之間對總銷售額的Joint effect，我們在特徵工程將商店與商品名稱所額外提供的資訊，像是城市，產品類別形成了新的變數。最後透過LightGBM經由gridsearch調整超參數後得到在LB的 rmse : 0.89258。                                                  

工作經歷

四月 2020 - 六月 2020

時間序列助教  國立交通大學

批改學生作業以及協助課業問題。

七月 2019 - 八月 2019

因子選股實習生  元大投信

利用統計方法幫助大中華團隊研究A股，挑選出重要因子且建構模型挑選股票。檢定因子間是否存在共線性，影響下一期報酬率估計。最後透過因子表現分成五組，回測並且比較各組表現。實習期間與主管配合良好，經理人提供想法以及自己的選股邏輯，我再透過檢定和回歸等相關統計方法實現，彼此互助學習讓我獲益良多。

七月 2016 - 八月 2016

顧問助理  VIT Advisors Limited(維億投資顧問有限公司)

陪同顧問到中國海口平安銀行做諮詢及授課，負責記錄諮詢重點。

Resume
Profile
Print

陳得翊 William

Data analyst, Machine learning engineer

我是一個熱愛挖掘潛在問題的統計人，以客觀的角度分析問題及處理，重視團隊合作，開放的態度分享彼此不同的想法和意見，有效率的解決問題。就學期間致力研究於機器學習，降維(Dimension Reduction)以及模型分類問題。並與台北榮民總醫院合作結合人工智慧開發全方位疾病診斷，在臨床上預測病人在一年內是否發生中風，以及是否由肺靜脈引起心房顫動的3D影像分類。

  

Mobile: +886-988-313-160

Email: [email protected]

技能

Python

  • 視覺化：Matplotlib, Seaborn


  • 機器學習套件：
    Tensorflow, Keras, Scikit-learn, Fast.ai, OpenCV

Machine Learning

  • 模型：Random Forest, XGBoost, LightGBM, SVM, CNN, RNN, LSTM, ResNet
  • 特徵選擇：Genetic algorithm, Simulated Annealing

Dimension Reduction

Multidimensional Scaling (MDS), SCMDS, Principal component analysis (PCA), Factor analysis model, Lasso regression

學歷

2018 - 2020

國立交通大學

統計學研究所

論文題目：Using Machine Learning Model and Ensemble Learning to Predict Ischemic stroke

第三屆統計研究成果研討會海報論文競賽—特優獎


2014 - 2018

私立淡江大學

統計學係

相關課程：回歸分析, 類別資料分析, 實驗設計, 無母數統計, 多變量分析, 時間序列, 倖存分析

程式：R, SAS (SAS Certified Base Programmer)

社團：統計系籃球隊-隊長                                           大統盃,亞軍, 2016 大統盃季軍, 2017

專案經驗

國立交通大學與台北榮民總醫院心臟科

預測病人在一年內是否發生中風Ischemic Stroke

                                                                

透過機器學習 (Machine Learning) 預測病人在一年內是否發生腦缺血型中風 (Ischemic stroke) 並且提升模型在 auc 上的表現。研究過程我們遇到資料極度不平衡的問題，透過變數選擇 (Feature Selection) 幫助我們挑選重要的特徵，使用集成學習 (Ensemble Learning)及下採樣 (Under-sampling)結合多個模型及處理資料不平衡的問題。

國立交通大學

Modeling High-dimensional time series by Structural factor model

                      

研究威爾夏5000指數 (Wilshire 5000 index) 成分股，透過主成份分析 (Principle Component Analysis) by Bai and Ng, Ratio-based method by Lam and Yao, and Structural factor model by Gao and Tsai, 找出背後影響5000支股票的潛在變數。對應於潛在變數與5000支股票的權重，得到新的一組投資組合，比較投組與指數的報酬。 


國立交通大學與台北榮民總醫院心臟科

CT Images Classification of PV and Non-PV trigger by 3D Convolution Network

                                                                                                

一位病人通常會有多張CT影像，有些影像包含疾病而有些影像則未包含， 使用3D CNN 可以使模型以病人為單位而非影像。在3D影像前處理對於像素的長寬和影像之間的切片厚度做歸一化。由於每位病人的影像張數不同， 在張數較少的病人上下補上黑色影像。在模型的選擇上使用 3D Resnet 做 模型訓練，針對資料不平衡的問題，我們對病人的影像做旋轉使得少數類 病人與多數類病人以相同比例進入模型。                                                              


Kaggle

Predict Future Sales (Top 8%)

                                                                                                

資料集由俄羅斯1C公司提供，紀錄2013/01~2015/10的日資料，目的是預測下個月每個產品和商店的總銷售額。在EDA探討各變數與總銷售額的marginal effect，以及變數之間對總銷售額的Joint effect，我們在特徵工程將商店與商品名稱所額外提供的資訊，像是城市，產品類別形成了新的變數。最後透過LightGBM經由gridsearch調整超參數後得到在LB的 rmse : 0.89258。                                                  

工作經歷

四月 2020 - 六月 2020

時間序列助教  國立交通大學

批改學生作業以及協助課業問題。

七月 2019 - 八月 2019

因子選股實習生  元大投信

利用統計方法幫助大中華團隊研究A股，挑選出重要因子且建構模型挑選股票。檢定因子間是否存在共線性，影響下一期報酬率估計。最後透過因子表現分成五組，回測並且比較各組表現。實習期間與主管配合良好，經理人提供想法以及自己的選股邏輯，我再透過檢定和回歸等相關統計方法實現，彼此互助學習讓我獲益良多。

七月 2016 - 八月 2016

顧問助理  VIT Advisors Limited(維億投資顧問有限公司)

陪同顧問到中國海口平安銀行做諮詢及授課，負責記錄諮詢重點。