Experience with data mining, machine learning, and web crawling. Hopes to focus more on data science and data engineer in future career.
• Analysis travel data and build a machine learning model. Estimating increase 4% orders (revenue).
• Maintain and develop an ETL distributed queuing system with 20 machines.
• Optimize the ETL system reduced more than 50% execution time.
• Develop new product crawler let product volume increase 1.5%.
• Making analysis charts provide for other departments.
Analysing G7 financial data. Model validation and parameter estimation by regression models ( SUR, MLE, Bootstrapping ). And comparing single equation estimators and confidence interval with system equation.
Calculus, Linear Algebra, Statistics.
Automatic crawling PTT data daily, and providing open data, more than six millions article, in MySQL.
Post-competition analysis, top 6% rank.
Highly imbalance data, ratio is 1000 : 1, 10 GB dataset size.
And the data is 50% missing value.
More than 4000 variables, but I build models by only 50 features.
Post-competition analysis, top 10% rank.
Time series problem. Building models predict sales after 48 days.
Post-competition analysis, top 8% rank.
Time series problem, eighty millions data size. Building models predict inventory demand after 2 weeks.
Real competition, top 25% rank.
Predicting which products will an consumer purchase again.
Python - numpy, pandas, sklearn, multiprocessing, joblib.
R - parallel, dplyr, data.table, mice.
Python - xgboost-gpu.
R - xgboost, svm, random forest, knn.
Python - kears-CNN.
R - GLM, GLMNET, NLS, SUR, MLE.
Major : Mathematics and Statistics.
R, Python. Basic in English and proficient in Chinese.