Please take the time browse around my website where you'll find some pretty awesome projects!
To navigate by programming language, please go to the "Projects" tab.
I've lived in the Bay Area for 10 years,
but I am always open to explore new places!
Go Gauchos!
Master's in Data Science, Class of 2024
I am currently working as a Marketing Consultant at Stiddle where I clean data and create data visualizations to present to the executive team so thay can make informed, data-driven decisions. As a diligent student, I am always hoping to learn more, especially in the data science and NLP field. I enjoy analyzing data to build the best models and bringing them to life by creating the most eye-catching visuals possible!
From the beginning to now
My interest in Data Science began as a History undergradate at UC Santa Barabara where where I learned how to perform Exploratory Data Analysis and webscrapping to find insights and critical information to help support my arguements. From there, my interest blossomed into an obsession!
Check out my projects!
To view my projects, please navigate to the tabs at the top of this page. Or click the button below for my suggestion on where to start! You will find many different types of projects from Exploratory Data Analysis to Data Modeling. You'll can also view my projects by the programming language I used to complete them!
In this project, I will identify the top three factors that contribute to turnover (backed up by evidence provided by analysis). The analysis is backed up by robust experimentation and appropriate visualization. Additionally, we also want to build a model that accurately predicts employee salary.
Build a model that get an estimate of how the SalePrice of the house is related to the square footage of the living area of the house and if the SalesPrice depends on which of 3 interested neighborhood the house is located in. Next, build the most predictive model with as many neccessary for sales prices of homes in all of Ames Iowa.
Assume that the audience is the CEO and CFO of Budweiser (your client) and that they only have had one class in statistics and have indicated that I cannot take more than 7 minutes of their time. They have hired you to address 9 questions / items.
Create an NLP pipeline to help people in needs
Create a machine learning/NLP pipeline to categorize these events and build a model to classify messages that are sent during disasters.
By classifying these messages, we can allow these messages to be sent to the appropriate disaster relief agency. The dataset -provided by Figure Eight- is used to build a model that classifies disaster messages, while the web app is where a respondent can input a new message and get classification results in several categories.