truongc2.github.io

About

My name is Richard Truong-Chau and I am currently a data scientist consultant at Maven Wave. I am passionate about applying machine learning to uncover meaningful insight in businesses and society.

This repository serves to track my progress in Data Science and to help organize my goals/projects. Feel free to get in touch if you want to collaborate or to speak more about my qualifications.

Projects

• Here I present my projects that focuses on exploratory data analysis and/or visualizations.
• The Notes section contains new tools that I used and issues that I encountered during the project.

Exploratory Data Analysis

Description	Datasets	Notes	Start Date	Last Update
Aircraft Wildlife Strikes	Wildlife Strikes from 1990-2015	Explore Pandas and visualization techniques	05.20.2018	05.22.2018
Analyzing 911 Calls	911 CSV	Pivot Tables and Timestamps	06.11.2018	06.13.2018
Financial Crisis	Data from Jan. 2006 to Jan. 2016	Pandas’ DataReader	06.13.2018	06.15.2018
Data Science For Good: NYC Specialized High School Exam	Census Data & SHSAT Registration	Interactive Plots (Plotly)	06.27.2018	07.05.2018

Machine Learning

In this section, I am mainly focused on machine learning projects that would help me learn new techniques/theories in practice.

Algorithm	Description	Datasets	Notes	Start Date	Last Update
Logistic Regression & Random Forest	Fatal Encounters with Police	US Census Data (4 files) and Fatal Encounters	Feature Engineering and visualizations	05.31.2018	06.27.2018
Linear Regression	Website or Mobile Apps	Ecommerce data	-	06.20.2018	06.20.2018
Logistic Regression	Ad click	Generated Advertisement Dataset	Heatmaps for Null Values and Get Dummies	06.21.2018	06.22.2018
K Nearest Neighbors	Predict Target Class	Generated Dataset	StandardScaler, Elbow Method	06.22.2018	06.23.2018
Decision Tree & Random Forest	LendingClub Loans	LendingClub data from 2007-2010	-	06.25.2018	06.27.2018
Natural Language Processing	Yelp Review	Yelp Review Ratings	-	06.28.2018	07.05.2018
PCA & Random Forest	Predict Costa Rican Poverty Levels	Kaggle	-	07.20.2018	07.26.2018
Random Forest & Logistic Regression	Predict Monetary Damage	NOAA Severe Earthquake Dataset	-	12.06.2018	12.12.2018

Stand Alone Projects

In this section, this is no general theme for the projects. It is just a showcase of my research and new tools that I wanted to test.

Goal	Description	Datasets	Notes	Start Date	Last Update
Characterize Mutations	Bioinformatics Research	Entire Salmonella Genome	Regular Expressions	08.23.2018	05.3.2018
Design, create, and implement a database	Biological Database	Files in PDF format	-	04.20.2018	05.09.2018
Webscrape	Webscrape IMDB Top 250 Movies	-	Beautifulsoup, request	05.25.2018	06.02.2018
Clothing Recommendation	Clothing classification and recommendation	Scraped data	Flask, Docker, Word Embeddings and Image Processing	12.26.2019	12.30.2019

Courses and Certificates

• Google Cloud Certified Professional Data Engineer
• Introduction to Computing: Engineering and Science (2016) (University of Illinois at Urbana-Champaign)
• Introduction to Databases (2018) (University of Illinois at Urbana-Champaign)
• Python for Data Science and Machine Learning Bootcamp (2018)

Sources

Interesting sources that I used along the journey.

Online Books

• Think Python How to Think Like a Computer Scientist
• Think Stats Exploratory Data Analysis in Python
• An Intro to Statistical Learning With Applications in R
• Fundamental of Database System 7th Edition

Blogs

• https://medium.com/@yurykashnitskiy
• https://www.dataquest.io/blog/data-science-portfolio-project/
• https://www.dataquest.io/blog/python-data-science/
• Kaggle Learn: Pandas, Data Visualizations, Machine Learning
• Datacamp:Python Exploratory Data Analysis, By Karlijn Willems

YouTube Channels

• Artificial Intelligence - All in One
• Socratica
• OMGenomics

CONTACT

I welcome any inquires or collaborations.

• E-mail: RTCrichard@gmail.com
• LinkedIn