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

 github.com/thenamecouldbeLiu

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