About Me

Computer Science graduate at University of Nevada, Las Vegas (UNLV) and a current Data Science student at University of Bellevue, Nebraska. Former designer and analyst at one of the most innovative companies in the world contributing for a brighter future. Always looking to learn, grow, and achieve my goals!

See Resume

Side Projects

Bill Splitter

This WebApp is used for groups who let one person pay a restaurant bill and the group splits the bill later on to pay back that person

Challenges

  • Creating a satisfying UI/UX.
  • Venmo button to lead to Venmo iOS app.
  • Adding elements on 'custom' option.

Notable Findings

Creating this project, I realized that UI/UX plays a big role when creating an app. If the user interface is confusing, the app becomes less interesting. This WebApp was also used for me to study JavaScript, HTML5, CSS3, and Bootstrap 5. There is still more work to do for this WebApp.

Technologies Used

  • JavaScript
  • Bootstrap 5
  • Git

In Progress

Source Code More Details

Tesla Solar Post-PTO Tool

This is a project that is used for the Post-PTO team of Tesla Solar. This WebApp is to determine part replacement for PV and Powerwall systems.

Challenges

  • Learning React for this project.
  • Connecting JavaScript with MS SQL
  • Interacting with Tesla GRID.

Notable Findings

This is my second WebApp project I've created. This time around, the UX/UI was better for my audience this time around. I believe it was because it was clear what my users wanted. This WebApp is created for me to study React JS and how to connect to the Tesla Solar database.

Technologies Used

  • JavaScript
  • Bootstrap 5
  • Git

Source Code & Details Restricted due to Data Privacy

Source Code More Details

Stock Portfolio Analysis

A project used to extract Robinhood portfolio and stocks historical datasets from Yahoo! Finance. Historical datasets are analyzed using methods, such as: Modern Portfolio Theory, Monte Carlo Simulations, Heatmaps, and Regression Graphs.

Challenges

  • Bugs when calculating fractional shares.
  • Transforming DataFrames.
  • Creating an automated dashboard.

Notable Findings

Calculating mean and standard deviation from historical datasets does not tell the whole story of the stock market, at least for short term. However, I have not gotten the chance to observe this program in long term. Sinec July 2020, I've created this program and so far it has given me great success of 25% return on my portfolio.

Technologies Used

  • Python
  • Jupyter Notebook
  • Git

Complete

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Flight Delays Analysis

A project used to analyze flight delays arriving in Las Vegas, NV (LAS) 2019. Datasets gathered from the Federal Aviation Administration (FAA) website are used to train the machine learning model in able to create predictions based on flight delays.

Challenges

  • Training the model.
  • Cleaning the datasets gathered from FAA.
  • Using cursor to integrate Python and PostgreSQL.

Notable Findings

Most origin location of delays are from SFO Airport and most airline company that has delays is Southwest Airlines. However, this is only in the month of January 2019. There is also an argument that since 40% of flights are Southwest Airlines, it's expected they would have more delays compared to other airlines.

Technologies Used

  • Python
  • PostgreSQL
  • Tabelau

In Progress

Source Code More Details