- Check raw data quality and source back to KR/JP data source to improve data quality
- EDA on large scale EC web record with pySpark, SQL to find insight
- Data visualization report & R dashboard with K8S
- Recommendation API service from scratch, including algorithm, ETL, API deployment, metrics
- Recommendation related metrics study, documentation from biz, model, UX aspects
- Recommendation system with spark.ml
- Python & R tutorial design
- Potential Customer Prediction with data pipeline using Azure
- Refactor Python feature engineering code into SQL, saving 80% computation time
- IoT data engineering & code refactor
- Research various deep learning embedding technique in NLP
- Web crawling of online journal paper
- Japanese English translation algorithm NLP research
- Build a web AI application which can classify over 100 categories of NIKE shoes
- Integrate front-end & model with python flask, numpy, pandas
- Design marketing plan and pitch this AI product to CEO
- Independent research of CV algorithm for better image segmentation performance
- Data cleaning & Feature engineering of large scale makeup shopping data
- Applied Xgboost algorithm to predict probability of buying each category of makeup for each customer
- Applied Cspade association algorithm to mine customer behavior and give recommendations to ad
- Build customer & inner-service chatbot from scratch
- Build automated program to produce daily recognition data analysis report with visualization.
- Linux OS Python environment building, Gitlab code version control
- App/ Software interface English/ Japanese translation
- R programming & Statistics Model Teaching
- Give advice of how to quantitatively analyze learners' result
- Fit & select various time series model for explain & prediction purpose
- Build a dashboard with R of real-time prediction & customer statistics
- Predict suitable plan for free user
- Predict user that may cancel in the next period based on behavior feature
- Use Google Universal Sentence Encoding to recommend song with lyrics
- Real time crawling of web data through user's query
- Build back-end system with cloud server Heroku and Python web framework "flask"
- Apply jieba package with pandas' vector computation to speed up reply time
- Data cleaning & Feature engineering of over 1,000,000 deposit, item shopping, login data
- Cluster user behavior with EM machine learning algorithm and make marketing plan for each group
- Build a recommendation system in Python to implement collaborative filtering (Test Accuracy: 90%).
(It was build as a web application with Flask, HTML, Jinja. It can be as designed as a API for game system)
- Stream over 30000 text data with Twitter API and process the text data
- Reduce dimension with t-SNE algorithm and plot the vector relation of emoji
- Predict emoji based on text with bag-of word and DNN, Xgboost.
- Collect fruit transaction data from public platform and crawl historical weather data
- Statistics test on various time variable to find significant ones
- Write into statistics report of how pricing of mango can be forecasted by my model
- Stream articles data from different forum and data cleaning
- Visualize word using behavior for different gender with wordcloud
(Males have more word about 'myself',, females have more word about "my boyfriends")
- Master degree of Service Science with major of information system & data analytics
- Course including quantitative and qualitative analysis method
- Represent NCCU as exchange student, studying global business, machine learning, information science
- Language Exchange program as English, Chinese teacher
- Course from basic to advance statistics, such as ANOVA, mathematical statistics.
Python: sklearn, tf, flask, pyspark, jieba, gensim, etc
R: ggplot, dplyr, various statistics model etc
SQL: MsSQL, NoSQL, HiveQL, SparkSQL
English
- TOEIC 945 [2018/7]
- TOEFL 97 [2016/9]
Japanese
- N1 152 / 180 [2018/7]
Coursera
- Natural Language Processing
- Sequence Model (deeplearning)
- Applied Machine Learning
- Bayesian Statistics
- Write Facebook Articles to promote each company to students
- Design virtual events to let students know more about the content about our event
- Collect questionnaires and visualize with R's ggplot2.
- Write Facebook Articles to promote the camp to high school student (Finally over 130 students enrolled)
- Track View data from Facebook backend to customize the article content
- Check raw data quality and source back to KR/JP data source to improve data quality
- EDA on large scale EC web record with pySpark, SQL to find insight
- Data visualization report & R dashboard with K8S
- Recommendation API service from scratch, including algorithm, ETL, API deployment, metrics
- Recommendation related metrics study, documentation from biz, model, UX aspects
- Recommendation system with spark.ml
- Python & R tutorial design
- Potential Customer Prediction with data pipeline using Azure
- Refactor Python feature engineering code into SQL, saving 80% computation time
- IoT data engineering & code refactor
- Research various deep learning embedding technique in NLP
- Web crawling of online journal paper
- Japanese English translation algorithm NLP research
- Build a web AI application which can classify over 100 categories of NIKE shoes
- Integrate front-end & model with python flask, numpy, pandas
- Design marketing plan and pitch this AI product to CEO
- Independent research of CV algorithm for better image segmentation performance
- Data cleaning & Feature engineering of large scale makeup shopping data
- Applied Xgboost algorithm to predict probability of buying each category of makeup for each customer
- Applied Cspade association algorithm to mine customer behavior and give recommendations to ad
- Build customer & inner-service chatbot from scratch
- Build automated program to produce daily recognition data analysis report with visualization.
- Linux OS Python environment building, Gitlab code version control
- App/ Software interface English/ Japanese translation
- R programming & Statistics Model Teaching
- Give advice of how to quantitatively analyze learners' result
- Fit & select various time series model for explain & prediction purpose
- Build a dashboard with R of real-time prediction & customer statistics
- Predict suitable plan for free user
- Predict user that may cancel in the next period based on behavior feature
- Use Google Universal Sentence Encoding to recommend song with lyrics
- Real time crawling of web data through user's query
- Build back-end system with cloud server Heroku and Python web framework "flask"
- Apply jieba package with pandas' vector computation to speed up reply time
- Data cleaning & Feature engineering of over 1,000,000 deposit, item shopping, login data
- Cluster user behavior with EM machine learning algorithm and make marketing plan for each group
- Build a recommendation system in Python to implement collaborative filtering (Test Accuracy: 90%).
(It was build as a web application with Flask, HTML, Jinja. It can be as designed as a API for game system)
- Stream over 30000 text data with Twitter API and process the text data
- Reduce dimension with t-SNE algorithm and plot the vector relation of emoji
- Predict emoji based on text with bag-of word and DNN, Xgboost.
- Collect fruit transaction data from public platform and crawl historical weather data
- Statistics test on various time variable to find significant ones
- Write into statistics report of how pricing of mango can be forecasted by my model
- Stream articles data from different forum and data cleaning
- Visualize word using behavior for different gender with wordcloud
(Males have more word about 'myself',, females have more word about "my boyfriends")
- Master degree of Service Science with major of information system & data analytics
- Course including quantitative and qualitative analysis method
- Represent NCCU as exchange student, studying global business, machine learning, information science
- Language Exchange program as English, Chinese teacher
- Course from basic to advance statistics, such as ANOVA, mathematical statistics.
Python: sklearn, tf, flask, pyspark, jieba, gensim, etc
R: ggplot, dplyr, various statistics model etc
SQL: MsSQL, NoSQL, HiveQL, SparkSQL
English
- TOEIC 945 [2018/7]
- TOEFL 97 [2016/9]
Japanese
- N1 152 / 180 [2018/7]
Coursera
- Natural Language Processing
- Sequence Model (deeplearning)
- Applied Machine Learning
- Bayesian Statistics
- Write Facebook Articles to promote each company to students
- Design virtual events to let students know more about the content about our event
- Collect questionnaires and visualize with R's ggplot2.
- Write Facebook Articles to promote the camp to high school student (Finally over 130 students enrolled)
- Track View data from Facebook backend to customize the article content