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职场能力评价定义
劉育志 (Liu Yu-Zhi)
NTU Information Management Graduate school
New Taipei City, Taiwan
◉ 3+ year Python
◉ SQL and ORM experiences
◉ Familiar with open source API
◉ Familiar with JavaScript
◉ Experience in using AWS, GCP
◉ Experience in using LINUX and shell
◉ TOEIC 900+
◉ Solution provider and self-motivator
Self-summary:
Decided to turn into software industry after 2 years of
marketing experience.
The experience makes me interesting in data processing,
and back-end engineering.
EDUCATION
National Taiwan University
Information Management
THESIS
Relationship between the emotions of a big chat group and the Taiwan stock
index Neural Network Model and predict future stock index
2020 - 2022
NCCU
Journalism and Economics
2013 - 2017
National Taiwan University of Science and Technology
Major: Industrial Management (Transfered to NCCU)
2013 - 2017
WORKING EXPERIENCES
Full-time Marketing Specialist • Nan-Ya Photonics Incorporation
Jun. 2018 - July 2020
In charge of advertisement, propaganda material, and any activities related to marketing
SIDE PROJECTS
Redfin data collection (Jan. 2021 ‒ Jun. 2021 )
◎ Helped Yi-Lin Tsai, the assistant professor of University of Delaware.
◎ GCP services such as virtual machines environment set-up, API applying and using.
◎ Scraping/automation framework: Selenium, BeautifulSoup. Multithreading
◎ Data cleaning framework: Pandas, Numpy.
GPT2 title generator (Mar. 2021 ‒ Jun. 2021 )
◎ Fine-tuning GPT2 as a generator of movie titles with the movie description as the input context.
◎ A flask backend and simple front-end system are built to present our results.
YouTube comment sentiment detection (Nov. 2020 ‒ Jan. 2021 )
◎ Youtube comments are collected using such as Selenium and BeautifulSoup.
◎ The collected data is used to train a sentiment classifier (SVM and Naïve Bayes).
Listoo! Backend (Sep. 2020 ‒ Dec. 2020 )
◎ Develop the web backend with Flask and SQL.
◎ Deploy RESTful API with Heroku.
Programing Skills
- C/C++: Algorithm and data structure (list, heap, hash map, set, Tree, sorting, search…), Standard Template Library
- Python: Flask backend framework, SQLAlchemy, Flask-SQLAlchemy, Pandas, Numpy
- Machine learning: Sklearn, Tensorflow/ Keras
SQL: SQlite, Postgresql, MariaDB - JAVA: Spring boot
- Frontend: HTML&CSS, JavaScript, Vue
Certificates
- TOEIC score: 910
edX courses: Algorithm and Data structure
劉育志 (Liu Yu-Zhi)
NTU Information Management Graduate school
New Taipei City, Taiwan
◉ 3+ year Python
◉ SQL and ORM experiences
◉ Familiar with open source API
◉ Familiar with JavaScript
◉ Experience in using AWS, GCP
◉ Experience in using LINUX and shell
◉ TOEIC 900+
◉ Solution provider and self-motivator
Self-summary:
Decided to turn into software industry after 2 years of
marketing experience.
The experience makes me interesting in data processing,
and back-end engineering.
EDUCATION
National Taiwan University
Information Management
THESIS
Relationship between the emotions of a big chat group and the Taiwan stock
index Neural Network Model and predict future stock index
2020 - 2022
NCCU
Journalism and Economics
2013 - 2017
National Taiwan University of Science and Technology
Major: Industrial Management (Transfered to NCCU)
2013 - 2017
WORKING EXPERIENCES
Full-time Marketing Specialist • Nan-Ya Photonics Incorporation
Jun. 2018 - July 2020
In charge of advertisement, propaganda material, and any activities related to marketing
SIDE PROJECTS
Redfin data collection (Jan. 2021 ‒ Jun. 2021 )
◎ Helped Yi-Lin Tsai, the assistant professor of University of Delaware.
◎ GCP services such as virtual machines environment set-up, API applying and using.
◎ Scraping/automation framework: Selenium, BeautifulSoup. Multithreading
◎ Data cleaning framework: Pandas, Numpy.
GPT2 title generator (Mar. 2021 ‒ Jun. 2021 )
◎ Fine-tuning GPT2 as a generator of movie titles with the movie description as the input context.
◎ A flask backend and simple front-end system are built to present our results.
YouTube comment sentiment detection (Nov. 2020 ‒ Jan. 2021 )
◎ Youtube comments are collected using such as Selenium and BeautifulSoup.
◎ The collected data is used to train a sentiment classifier (SVM and Naïve Bayes).
Listoo! Backend (Sep. 2020 ‒ Dec. 2020 )
◎ Develop the web backend with Flask and SQL.
◎ Deploy RESTful API with Heroku.
Programing Skills
- C/C++: Algorithm and data structure (list, heap, hash map, set, Tree, sorting, search…), Standard Template Library
- Python: Flask backend framework, SQLAlchemy, Flask-SQLAlchemy, Pandas, Numpy
- Machine learning: Sklearn, Tensorflow/ Keras
SQL: SQlite, Postgresql, MariaDB - JAVA: Spring boot
- Frontend: HTML&CSS, JavaScript, Vue
Certificates
- TOEIC score: 910
edX courses: Algorithm and Data structure