In this project, I use IMDB movie reivews sentiment classification (included in Keras) with 50,000 movie reviews that individually scored as positive (1) or negative (0). The dataset is divided into 25,000 reviews for training, 25,000 for testing. The outcome is to use our model to predict that a free form text from user input is a negative or positive comment/review.

In this project, I will develop binary classifier model to predict the flight will be on-time or late. I also run the performance metric to analyze the precision of the model.

Using 2 datasets from Kaggle with information about applications listed on the 2 most popular mobile app stores, I cleaned any unwanted data, remove non-English app and standardize application name to remove duplication. Next, I analyze applications' rating by app category, and suggest some category that we can develop our app to be profitable.

In this project, I developed a web application for a fictional clothing store called Rainbow using React

Using Tableau to visualize a data set about amount of time spend on sleep among American age groups.

In this project, I built a Power BI report to analyze sale data from AdventureWorks sample dataset from Microsoft.