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4-6 năm
6-10 năm
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國立成功大學
Avatar of 王廷軒.
Avatar of 王廷軒.
Past
副研究員 @財團法人台灣綜合研究院研究四所
2021 ~ 2021
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
Trong vòng một tháng
人工智慧 AI 預計以基因演算法(博士論文)為出發點,進行下列內容 1. AI / 研究、開發、優化演算法,或相關應用和服務 2. AI / 參與智慧製造、智慧醫療、智慧生活、智慧企業等專案,並協助設計分析流程(含數據與資料採集、演算法選用等) 3. AI /
數據分析與視覺化
系統設計
資料庫程式設計
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Full-time / Quan tâm đến làm việc từ xa
4-6 năm
國立成功大學
資源工程學系

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Definition of Reputation Credits

Technical Skills
Specialized knowledge and expertise within the profession (e.g. familiar with SEO and use of related tools).
Problem-Solving
Ability to identify, analyze, and prepare solutions to problems.
Adaptability
Ability to navigate unexpected situations; and keep up with shifting priorities, projects, clients, and technology.
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Trong vòng một tháng
Software Engineer
Synpulse
2022 ~ Hiện tại
台灣台中市
Professional Background
Tình trạng hiện tại
Đã có việc làm
Tiến trình tìm việc
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Data Scientist, Software Engineer
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Trí tuệ nhân tạo/ Máy học
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2-4 năm
Management
Chưa có
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python
SQL
Machine Learning
Bash
postgres
Docker
PL\SQL
Oracle Database
Ngôn ngữ
English
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Data Engineer/Data Analyst/Data Scientist
Loại hình công việc
Full-time
Địa điểm
台灣台中市
Làm việc từ xa
Quan tâm đến làm việc từ xa
Freelance
Học vấn
Trường học
國立成功大學
Chuyên ngành
工程科學
In
Zxcfjm0pllq5klucgpcd

Laurence Lin

Enthusiastic data scientist, willing to bring up AI solutions that would solve human life problems. Highly cooperative teamwork and curious about data insight information. Familiar with Python and SQL language, experienced of image processing and time series forecasting. Understand basic web development and RESTful API with Flask or FastAPI framework.


Taichung city,Taiwan

Email: [email protected]

Cell Phone: 0916-067399

Github: https://github.com/laurence-lin

LinkedIn:https://www.linkedin.com/in/laurence-lin-836412133/

Medium: https://lawrence123.medium.com/

Working Experience


Machine learning engineer (2020/09/01 ~ current) 

Hamastar Technology Corporation

Build data science application platform for data science developers and end users 

Develop data science solutions for web layout defect detection, save 70% of time for developers to examine the product


Skills


Programming: Python, R, SQL 
Machine Learning: Regression, Classification, Time Series Forecasting 
Framework: Scikit-learn, Keras, PyTorch 
Web Development: html, css, RESTful API 
Web Scraping: Selenium 
Data Visualization: Tableau


Projects


Retail Store Location Selection by Popularity Ranking: Collect geographic features from Foursquare API and Google Place API, use EDA for data analysis and preprocessing, build predictive model to rank the store popularity, and found the main characteristics that effects most of the retail store's popularity. Achieve 0.83 in NDCG@k metric comparable with previous research.

Methods: EDA, Google Place API, Foursquare API, SVR, Linear Regression, Neural Network

link: https://github.com/laurence-lin/Retail-Store-Location-Ranking


Credit Card Fraud Detection:  Predict the probability for credit card data fraud, apply feature engineering for data cleaning and transformation, use cross validation and ROC_AUC as evaluation for model performance.

Methods: EDA, LightGBM, Cross Validation, Logistic Regression

link: https://github.com/laurence-lin/Kaggle_competition/blob/master/FraudDetect/FraudDetection.ipynb

Projects


Retail Store Location Selection by Popularity Ranking: Collect geographic features from Foursquare API and Google Place API, use EDA for data analysis and preprocessing, build predictive model to rank the store popularity, and found the main characteristics that effects most of the retail store's popularity. Achieve 0.83 in NDCG@k metric comparable with previous research.

Methods: EDA, Google Place API, Foursquare API, SVR, Linear Regression, Neural Network

link: https://github.com/laurence-lin/Retail-Store-Location-Ranking


Credit Card Fraud Detection:  Predict the probability for credit card data fraud, apply feature engineering for data cleaning and transformation, use cross validation and ROC_AUC as evaluation for model performance.

Methods: EDA, LightGBM, Cross Validation, Logistic Regression

link: https://github.com/laurence-lin/Kaggle_competition/blob/master/FraudDetect/FraudDetection.ipynb

Education


IBM Data Science Professional(Certified) 

Coursera, June 2020 ~ August 2020

Google Data Analytics(Certified)

Coursera, April 2021 ~ June 2021

National Cheng Kung University / Engineering Science / Bachelor's degree

國立成功大學工程科學系

National Cheng Kung University / Engineering Science / Master degree

國立成功大學工程科學所

Master thesis: PM 2.5 forecasting using LSTM model


Resume
Hồ sơ của tôi
Zxcfjm0pllq5klucgpcd

Laurence Lin

Enthusiastic data scientist, willing to bring up AI solutions that would solve human life problems. Highly cooperative teamwork and curious about data insight information. Familiar with Python and SQL language, experienced of image processing and time series forecasting. Understand basic web development and RESTful API with Flask or FastAPI framework.


Taichung city,Taiwan

Email: [email protected]

Cell Phone: 0916-067399

Github: https://github.com/laurence-lin

LinkedIn:https://www.linkedin.com/in/laurence-lin-836412133/

Medium: https://lawrence123.medium.com/

Working Experience


Machine learning engineer (2020/09/01 ~ current) 

Hamastar Technology Corporation

Build data science application platform for data science developers and end users 

Develop data science solutions for web layout defect detection, save 70% of time for developers to examine the product


Skills


Programming: Python, R, SQL 
Machine Learning: Regression, Classification, Time Series Forecasting 
Framework: Scikit-learn, Keras, PyTorch 
Web Development: html, css, RESTful API 
Web Scraping: Selenium 
Data Visualization: Tableau


Projects


Retail Store Location Selection by Popularity Ranking: Collect geographic features from Foursquare API and Google Place API, use EDA for data analysis and preprocessing, build predictive model to rank the store popularity, and found the main characteristics that effects most of the retail store's popularity. Achieve 0.83 in NDCG@k metric comparable with previous research.

Methods: EDA, Google Place API, Foursquare API, SVR, Linear Regression, Neural Network

link: https://github.com/laurence-lin/Retail-Store-Location-Ranking


Credit Card Fraud Detection:  Predict the probability for credit card data fraud, apply feature engineering for data cleaning and transformation, use cross validation and ROC_AUC as evaluation for model performance.

Methods: EDA, LightGBM, Cross Validation, Logistic Regression

link: https://github.com/laurence-lin/Kaggle_competition/blob/master/FraudDetect/FraudDetection.ipynb

Projects


Retail Store Location Selection by Popularity Ranking: Collect geographic features from Foursquare API and Google Place API, use EDA for data analysis and preprocessing, build predictive model to rank the store popularity, and found the main characteristics that effects most of the retail store's popularity. Achieve 0.83 in NDCG@k metric comparable with previous research.

Methods: EDA, Google Place API, Foursquare API, SVR, Linear Regression, Neural Network

link: https://github.com/laurence-lin/Retail-Store-Location-Ranking


Credit Card Fraud Detection:  Predict the probability for credit card data fraud, apply feature engineering for data cleaning and transformation, use cross validation and ROC_AUC as evaluation for model performance.

Methods: EDA, LightGBM, Cross Validation, Logistic Regression

link: https://github.com/laurence-lin/Kaggle_competition/blob/master/FraudDetect/FraudDetection.ipynb

Education


IBM Data Science Professional(Certified) 

Coursera, June 2020 ~ August 2020

Google Data Analytics(Certified)

Coursera, April 2021 ~ June 2021

National Cheng Kung University / Engineering Science / Bachelor's degree

國立成功大學工程科學系

National Cheng Kung University / Engineering Science / Master degree

國立成功大學工程科學所

Master thesis: PM 2.5 forecasting using LSTM model