Project 1: People Salary Predict Project

• Built several Machine Learning models (Logistic Regression, RandomFordst, and XGboost) to predict whether a person makes over 50K a year
• Several Feature Engineering methods to fill with columns that have NA values.
• 8th in the Kaggle competion

Project 2: Loan Denied Project

• Built several Neural Network and Machine Learning models (ANN, RandomFordst, and XGboost) to predict whether the bank should deny the loan application
• Data processing to transform datas and several Feature Engineering methods to fill with columns that have NA values.
• 3th in the kaggle competition

Project 3: (1dCNN, 1dRNN) + NLP Project

• Built several Machine Learning models (NLP) and Neural Network models (CNN, RNN) to predict types of meals do people eat base on foods name
• Built Feature Engineering methods to give data new feature.

Project 4: Image Recognition Project

• Built several CNN models to predict Image-Recognition.
• Data processing to transform training and testing dataset.

Project 5: Big Data Project (NLP and Recommendation System for beer)

• Big data (2G) cleaning and data wrangling
• Built Recommendation System by built NLP
• As a team leader, successfully assigned each member work content

Project 6: ESPN FootballData Analyze Project

• Create Web Scraping methods to grab ESPN Football data, Found the API hidden pattern, and automize the grab process.
• Built a data cleaning process and give the company the real important results.
• Made Poisson and Logistic regression models to predict the game in a different aspect.
• Automize the Excel process to produce the report more efficiently.