Full Stack Developer & Data Engineer, primarily using Python. At work, as for BackEnd have written TypeScript and now using Go, for FrontEnd, have handled Vue and React. And for data use Java for Flink and Spark previously. Forcing on learning AI models and conducting research in Natural Language Processing.
- TypeScript/Express - Http Time Api (moment)
- TypeScript/Express - Http File Api (file)
- TypeScript/Express - Hospital Fee Api (mariadb/typeorm/testing)
- TypeScript/Express - Hospital Register Api (mariadb/typeorm)
- Go/Fiber - User Api (mongodb/testing/error code)
- Go/Gin - Permission Api (mongodb/error code/viper/login/permission)
- Go/Gin - IPFS File Api (postgres/ipfs/file server)
- Python/Django - Library Api (mysql/error code)
- TypeScript/Express - Accounting Api (mariadb/typeorm/cronJob/error handling)
- JavaScript/Vue3 - Accounting Web (pie chart)
- Python/Flask - Cafe Map Server (map)
- GCP/Flink - Deploy Flink
- Java/Flink - Data Pipeline Kafka (kafka/doris/mongoDB)
- Python/Logistic Regression - Titanic (sklearn/logistic regression)
- Python/Decision Tree - Iris Classification (sklearn/decision tree)
- Python/XGBRegressor - Avocado Prices (xgbRegressor/grid search cv)
- Python/Random Forest - Red Wine Quality (sklearn/random forest)
- Python/XGBRegressor & LightGBMRegressor - House Prices (xgbRegressor/lightGBMRegressor)
- Python/Support Vector Classification - Breast Cancer Wisconsin (support vector classification)
- Python/CNN - Digit Recognition (tensorflow/data augmentation/cnn)
- Python/CNN/ResNet50 - Cat And Dog Classification (tensorflow/data augmentation/cnn/resNet50)
- Python/Latent Dirichlet Allocation - Topic Modeling (word cloud)
- Python/CBOW - Word2Vec And PCA (pca/kmeans)
- Python/Roberta - Sentiment Analysis (finetune/chinese)
- Python - Popcat Click (selenium)
- Python - PTT Gossiping Crawling (requests)
- Python - Project Gutenberg Crawling (requests/regex)
- Python - Youtube Crawling (selenium/yt-dlp)