Expertise: Machine Learning, Data Analysis, Algorithm Design Personality: Efficient, Focused, Cooperative, Patient.
I've already performed my military service.
I am a recent graduate of Cheng Kung University's Department of Geomatics, and I expect to graduate in August 2020. I am familiar with Python, Java, C, and other languages. I am interested in data analysis and enjoy organizing and maintaining data from different sources. When I find trends and correlations in different data and apply these patterns to problems will give me a strong sense of accomplishment. Enjoys learning new technologies, understanding algorithms quickly, and continually refining skills.
Bachelor of Computer Science, Feng Chia University, Taichung, Taiwan
Skyline Query for Multi-Request Route Planning with Time Constraint
Motion Recognition System (JARVISH) based on triaxial accelerometer signals mounted on the helmet.
GIS WEB design
Escape route planning
Pandas、NumPy、scikit-learn、TensorFlow 、pytorch、requests、opencv、Matplotlib、Beautiful Soup
C、C++、Java、SQL、R
MySQL
git、SourceTree
English
Mandarin
Crawler
Mahjong
My name is Liang Yun Chen, and I wanted to be an IT engineer since I was a kid because I thought I could play with computers. I have studied C language in high school, but I didn't realize it was what I thought it would be until I went to college to study Computer Science. My interest in data analysis and data processing deepened during my studies, and I want to become an information technology engineer even more.
I am goal orientated, efficient, highly focused, and observant—ideal for work related to data analysis.
I graduated from Feng Chia University with a degree in Computer Science and completed my Master's degree in the Department of Geomatics at National Cheng Kung University.
In college, I built up necessary programming skills and learned Java, C, C++, and Python, R, and database design in my senior year of college, and built up a basic understanding of machine learning and neural network algorithms through Python. I joined the Mining and Applications on Geospatial Information Computing Laboratory to refine the skills in data mining and algorithm design.
During my master's degree, I worked on designing algorithms related to the Internet of Things (IoT) in the lab. I also have a deeper understanding of basic machine learning methods such as K-means, Bayesian classification, decision tree classification, and neural network design methods such as DNN, CNN, RNN, etc. My thesis research topic is related to the skyline query, an algorithm used in multi-decisional systems. I think it can be used in different ways, such as pre-processing data and correlation analysis to filter out useful features.
In the future, I will continue to improve my knowledge of machine learning and deep learning. I am currently working on the Slide Project on image recognition. The main problem is that it is easy to over-fit the test data for deep learning object recognition, especially the influence of the background. It would be a significant breakthrough if we can find a way to generate data that can improve the model's stability.
Expertise: Machine Learning, Data Analysis, Algorithm Design Personality: Efficient, Focused, Cooperative, Patient.
I've already performed my military service.
I am a recent graduate of Cheng Kung University's Department of Geomatics, and I expect to graduate in August 2020. I am familiar with Python, Java, C, and other languages. I am interested in data analysis and enjoy organizing and maintaining data from different sources. When I find trends and correlations in different data and apply these patterns to problems will give me a strong sense of accomplishment. Enjoys learning new technologies, understanding algorithms quickly, and continually refining skills.
Bachelor of Computer Science, Feng Chia University, Taichung, Taiwan
Skyline Query for Multi-Request Route Planning with Time Constraint
Motion Recognition System (JARVISH) based on triaxial accelerometer signals mounted on the helmet.
GIS WEB design
Escape route planning
Pandas、NumPy、scikit-learn、TensorFlow 、pytorch、requests、opencv、Matplotlib、Beautiful Soup
C、C++、Java、SQL、R
MySQL
git、SourceTree
English
Mandarin
Crawler
Mahjong
My name is Liang Yun Chen, and I wanted to be an IT engineer since I was a kid because I thought I could play with computers. I have studied C language in high school, but I didn't realize it was what I thought it would be until I went to college to study Computer Science. My interest in data analysis and data processing deepened during my studies, and I want to become an information technology engineer even more.
I am goal orientated, efficient, highly focused, and observant—ideal for work related to data analysis.
I graduated from Feng Chia University with a degree in Computer Science and completed my Master's degree in the Department of Geomatics at National Cheng Kung University.
In college, I built up necessary programming skills and learned Java, C, C++, and Python, R, and database design in my senior year of college, and built up a basic understanding of machine learning and neural network algorithms through Python. I joined the Mining and Applications on Geospatial Information Computing Laboratory to refine the skills in data mining and algorithm design.
During my master's degree, I worked on designing algorithms related to the Internet of Things (IoT) in the lab. I also have a deeper understanding of basic machine learning methods such as K-means, Bayesian classification, decision tree classification, and neural network design methods such as DNN, CNN, RNN, etc. My thesis research topic is related to the skyline query, an algorithm used in multi-decisional systems. I think it can be used in different ways, such as pre-processing data and correlation analysis to filter out useful features.
In the future, I will continue to improve my knowledge of machine learning and deep learning. I am currently working on the Slide Project on image recognition. The main problem is that it is easy to over-fit the test data for deep learning object recognition, especially the influence of the background. It would be a significant breakthrough if we can find a way to generate data that can improve the model's stability.