- Việc làm
CVTạo CV online chuyên nghiệp, miễn phí
PortfolioTrình bày kỹ năng chuyên môn và dự án đã thực hiện một cách sinh động, trực quan.CVTạo CV online chuyên nghiệp, miễn phíTạo CVTạo CV online chuyên nghiệp, miễn phíMẫu CVTruy cập kho mẫu CV online ấn tượng, chuẩn quốc tế.CV mẫuTham khảo các CV mẫu đẹp đã được người dùng CakeResume ứng tuyển thành công.Cẩm nang nghề nghiệpTìm hiểu cách viết CV cho từng ngành nghề và vị trí.Trợ giúp viết CVTham khảo lời khuyên từ các chuyên gia tuyển dụng của CakeResume.- Kho tài nguyênCẩm nang ứng viênThế giới công sởVề đối tácCẩm nang doanh nghiệpVề CakeResumeBài viết nổi bật
- Tuyển dụng
- Tải app CakeResume
CakeResume Talent Search
Kế hoạch tuyển dụng đơn giản và hiệu quả nhất
Tìm kiếm 40k+ CV và chủ động liên hệ với ứng viên để đạt hiệu quả tuyển dụng cao hơn. Sự lựa chọn của hàng trăm công ty.
- Duyệt tất cả kết quả tìm kiếm
- Bắt đầu trò chuyện không giới hạn
- CV chỉ có thể truy cập bởi các công ty trả phí
- Xem địa chỉ email và số điện thoại của người dùng
Definition of Reputation Credits
[email protected]
0961 100 735, Hsinchu, Taiwan
Work Experience
June 2021 — August 2021
Software Engineering Internship at HTC
- Responsible for writing automated tests using Robot Framework, a test automation framework based on Selenium.
- Worked on a UI test for the VIVE UK home page that verifies texts are correct, images can load properly, links and buttons lead to a working page, and forms are able to submit.
- Worked on an API test for the VIVE UK Accessories page that verifies the product prices displayed are the correct prices received from the API.
Education
September 2018 — Present, expected to graduate in June 2022.
BS, Computer Science, National Tsing Hua University
Current GPA - 3.97
Relevant Skills and Courses:
— Python, C++, C, SQL — Data Structures and Algorithms
— Keras, Pytorch, Scikit-learn — Git Version Control
— Data Science — Database Systems
Projects
3D Tic-Tac-Toe with Monte Carlo Tree Search
Applied the Monte Carlo Tree Search with Upper Confidence Bound applied for Trees on a 4 by 4 by 4 Tic-Tac-Toe state space to create an agent that calculates the next optimal move which resulted in a more than 100%-win rate when faced against a Random Agent.
Image Classifier with ResNet
Developed an image classifier in python using the fast.ai library with training data taken from Bing image search by fine-tuning the ResNet model, which resulted in a prediction accuracy higher than 90%.
Tic-Tac-Toe agent with Reinforcement Learning
Designed a Tic-Tac-Toe agent by learning state values from over 50,000 iterations of playing against itself and applying the Monte Carlo algorithm, which resulted in an unbeatable agent.
COVID-19 30-day Mortality Prediction from CXR
Built a CNN model by using Keras in the Tensorflow library with three hidden layers, which predicts a 30-day mortality from CXR which had a 0.75 F1 score.
Pathfinding Visualizer
Designed and built a program with python to visualize pathfinding in a randomly generated maze using Kruskal's Algorithm, Bellman-Ford and A* Search algorithms.
[email protected]
0961 100 735, Hsinchu, Taiwan
Work Experience
June 2021 — August 2021
Software Engineering Internship at HTC
- Responsible for writing automated tests using Robot Framework, a test automation framework based on Selenium.
- Worked on a UI test for the VIVE UK home page that verifies texts are correct, images can load properly, links and buttons lead to a working page, and forms are able to submit.
- Worked on an API test for the VIVE UK Accessories page that verifies the product prices displayed are the correct prices received from the API.
Education
September 2018 — Present, expected to graduate in June 2022.
BS, Computer Science, National Tsing Hua University
Current GPA - 3.97
Relevant Skills and Courses:
— Python, C++, C, SQL — Data Structures and Algorithms
— Keras, Pytorch, Scikit-learn — Git Version Control
— Data Science — Database Systems
Projects
3D Tic-Tac-Toe with Monte Carlo Tree Search
Applied the Monte Carlo Tree Search with Upper Confidence Bound applied for Trees on a 4 by 4 by 4 Tic-Tac-Toe state space to create an agent that calculates the next optimal move which resulted in a more than 100%-win rate when faced against a Random Agent.
Image Classifier with ResNet
Developed an image classifier in python using the fast.ai library with training data taken from Bing image search by fine-tuning the ResNet model, which resulted in a prediction accuracy higher than 90%.
Tic-Tac-Toe agent with Reinforcement Learning
Designed a Tic-Tac-Toe agent by learning state values from over 50,000 iterations of playing against itself and applying the Monte Carlo algorithm, which resulted in an unbeatable agent.
COVID-19 30-day Mortality Prediction from CXR
Built a CNN model by using Keras in the Tensorflow library with three hidden layers, which predicts a 30-day mortality from CXR which had a 0.75 F1 score.
Pathfinding Visualizer
Designed and built a program with python to visualize pathfinding in a randomly generated maze using Kruskal's Algorithm, Bellman-Ford and A* Search algorithms.