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4-6 years
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More than 15 years
A.I Reseacher @Taipei Medical University2019 ~ Present
・
Algorithm Engineer/ Data Scientist/ Sr. Project Management
More than one year
Duc. Nguyen + 5-year experience in product & data field + Machine Learning/Deep Learning/Natural Language Processing + Python/R/SQL/Javascript + Qlik Sense/Tableau/PowerBI/Metabase Product Manager, Data Science City, TW [email protected] Work Experience Taipei Medical University, A.I Reseacher, Aug 2019 ~ Present ✓ A member of Natural Language Processing Lab ✓ Applying new state-of-the-art models such as ELMO, BERT, RoBERTa to get better accuracy or f1-score on public datasets ✓ Developing a system architecture of Big Data
Full-time / Interested in working remotely
4-6 years
Taipei Medical University
・
Data Science
Software Developer @BODC2012 ~ 2014
・
AI Software Engineer,Deep learning Engineer
More than one year
Full-time
6-10 years
Minia University
・
Math And Computer ScienceFull-time / Interested in working remotely
6-10 years
NCUE
・
物理Not open to opportunities
Full-time / Interested in working remotely
6-10 years
大同大學
・
事業經營系
Past
Service Provider @Taron Solutions Limited2023 ~ 2023
・
AI工程師、機器學習工程師、電腦視覺工程師、資料科學家、Machine Learning Engineer、Computer Vision Engineer、Data Scientist
Within one month
醫院 二月七月 2020 • 開發x光片器官辨識系統，透過分類模型判斷所拍攝的器官是否符合醫生要求，系統正確率高達96%。 技術：TensorFlow、Google Inception v3 運算思維與程式設計 課程助教 • 東海大學 Tunghai University 九月七月 2020 • 協助修課同學培養程式設計邏輯，並實作C/C++
Unemployed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
國立臺北科技大學
・
資訊工程
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
Employed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
國立政治大學（National Chengchi University）
・
資訊科學系
Firmware Engineer @Lanner Electronics Inc.2021 ~ Present
・
Firmware Engineer, Firmware Developer, Embedded Software Engineer
Within one month
蕭舜誠-Shawn New Taipei City, [email protected] Hi, I’m Shawn. experienced firmware engineer with nearly five years of experties. 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
Employed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
國立高雄科技大學（原國立高雄第一科技大學）
・
電子工程
Data science lecturer @Ittraining2020 ~ Present
・
Data Scientist 資料科學家_數據分析師
Within one month
HUEY-LONG CHEN 陳惠龍 Kaggle Competitions Expert: https://www.kaggle.com/alanchen1115 Competitions: NLP (自然語言處理): - Silver medal (solo): (Kaggle) The Learning Agency Lab - PII Data Detection: Develop automated techniques to detect and remove PII from educational data. 2024/04/24 - Silver medal (solo): (Kaggle) U.S. Patent Phrase to Phrase Matching: Help Identify Similar Phrases in U.S. Patents, 2022/06/21 Recommendation system (推薦系統): - Silver medal (solo): (Kaggle) OTTO – Multi-Objective Recommender System: Build a
Employed
・
Open to opportunities
Part-time / Interested in working remotely
More than 15 years
Purdue University
・
School of civil engineering (Stochastic & statistical hydrology)
Team Lead @工業技術研究院2020 ~ Present
・
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
隊 溝通協作能力的問題解決者。 [email protected] 技能 程式開發 C++, Python, Matlab Git, Docker Linux, Windows ROS, ROS2 深度學習/機器學習 框架: DarkNet(Yolo), Keras/Tensorflow, TensorRT 應用: Object Detection, Classification, Sensor Fusion 電腦視覺 影像處理: OpenCV, NVIDIA NPP 點雲處理: PCL 語言 中文 (母語) 英文 (TOEIC 725) 韓文 (初等) 工作經歷 Team Lead • 工業技術研
Employed
・
Open to opportunities
Full-time / Interested in working remotely
6-10 years
National Chung Cheng University
・
資訊工程學所
Senior Specialist Consultant @HSBC Software Dev(GD) Ltd.2021 ~ Present
・
Software Manager
Within two months
CHUNG-LIANG PAN Over 10 years software develop experience which including embedded system, cloud service platform building(data collect and analyse, commercial platform, photo recognised ) and apps developing. Currently i am leading a software team in to build and running a global finance system which handle huge amount of trades and settlements. Senior Specialist Consultant Guangzhou, 廣東省 China [email protected] Mobile:Skills Languages & Frameworks Experience in java,C ,C++,Python, Bash,Javascript,html,css Front-end Frameworks : Bootstrap,DirectFB,FFmpeg, OpenGL,Canvas Back-end Frameworks : SpringCloud,Jersey,Tomcat,nginx, swagger,vert
Employed
・
Open to opportunities
Full-time / Interested in working remotely
10-15 years
National Taiwan Ocen University
・
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Data Engineer, Data Scientist, DevOps / System Admin
Fields of Employment
Big Data, Artificial Intelligence / Machine Learning, Semiconductor
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2-4 years
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I've had experience in managing 1-5 people
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National Taiwan University
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Mechanical Engineering
Kao Chiang
NTU ME
#ML #NLP #Recommender
Skills
Software
> ML: Tensorflow, Keras, Xgboost,
LightGBM, Pytorch
> NLP: Rasa, spaCy, Gensim, GluonNLP, GloVe
> Web: Flask, Django, Vue, SQL
> APP: Swift, Android Studio
> Others: Docker, docker-compose, Spark
Combination
There are lots of open source tools and platforms to help us to develop the project, but how to combine each tool or platform well (efficiency & security) is the point.
With some experience of organizing an whole project by myself, I am good at making good use of the newest technology to solve the problems.
Communication
Nowadays, it is quite easy to use many powerful tools, but mostly each of them are used in different platform or languange, and each of tools often include many knowledge which need to be considered various aspects. In some experience of system design, I
Projects
Chatbot
An end-to-end chatbot platform which includes two part of main services. One is a friendly interface to edit corpus and dictionary for training machine-learning model; Another platform is a chatbot services include chat room for testing , logging for remarking incorrect response, and so on. Most of NLP models are applied in English or western language, but our clients are Chinese. So, I need to re-write many program flow to be suitable and well on Chinese .Face Recognition
In a corporation with a security company, they want to include some AI in their security system in an exhibition. There are two main of conditions. One is to apply in department store to recognize and record the flow of people with gender and age instantly. The other one is an access control by recognize face of people.
To their demand, we make a device embedding two machine learning model to detect face and recognize age and gender.
Recommender System
It is lucky to participate the design of recommender system of a top e-commerce platform, and that is the first time I took "big data". Because of the amount of data, the data pipeline need to be very careful in the parallel computing. We use Apache Spark framework and Kubernetes to deploy our models.
The recommender system is mainly combined by two models. One model is user-based model and the other is content-based model. We use fully-connected layer to combine.
Kao Chiang
NTU ME
#ML #NLP #Recommender
Skills
Software
> ML: Tensorflow, Keras, Xgboost,
LightGBM, Pytorch
> NLP: Rasa, spaCy, Gensim, GluonNLP, GloVe
> Web: Flask, Django, Vue, SQL
> APP: Swift, Android Studio
> Others: Docker, docker-compose, Spark
Combination
There are lots of open source tools and platforms to help us to develop the project, but how to combine each tool or platform well (efficiency & security) is the point.
With some experience of organizing an whole project by myself, I am good at making good use of the newest technology to solve the problems.
Communication
Nowadays, it is quite easy to use many powerful tools, but mostly each of them are used in different platform or languange, and each of tools often include many knowledge which need to be considered various aspects. In some experience of system design, I
Projects
Chatbot
An end-to-end chatbot platform which includes two part of main services. One is a friendly interface to edit corpus and dictionary for training machine-learning model; Another platform is a chatbot services include chat room for testing , logging for remarking incorrect response, and so on. Most of NLP models are applied in English or western language, but our clients are Chinese. So, I need to re-write many program flow to be suitable and well on Chinese .Face Recognition
In a corporation with a security company, they want to include some AI in their security system in an exhibition. There are two main of conditions. One is to apply in department store to recognize and record the flow of people with gender and age instantly. The other one is an access control by recognize face of people.
To their demand, we make a device embedding two machine learning model to detect face and recognize age and gender.
Recommender System
It is lucky to participate the design of recommender system of a top e-commerce platform, and that is the first time I took "big data". Because of the amount of data, the data pipeline need to be very careful in the parallel computing. We use Apache Spark framework and Kubernetes to deploy our models.
The recommender system is mainly combined by two models. One model is user-based model and the other is content-based model. We use fully-connected layer to combine.