Personal Details

In the information age, anyone can learn anything if they have passion and dedication.

At the beginning of 2018 I started teaching myself how to code in Python. Shortly thereafter, I left my corporate job, got a part-time job at a daycare, and started studying data-science and software engineering full time. My passion sustained me. I spent many night in front of a computer screen, studying coding tutorials and discussing on data science forums.

I still treat every day as an opportunity to learn something new. Recently, I have started working as a data science freelancer for various research teams and businesses across the US. I am also pursuing a computer science Masters at the University of Texas at Dallas.

Over the next few months I will be interning at Sprint as a data scientist.

About me

Data Analytics

The first step in building amazing machine learning applications is collecting and understanding data.


I build intelligent systems that use text and speech data to understand, describe, and interact with people.

Machine Learning

I have a deep understanding of the theory, implementation, and best practices that make machine learning applications successful.

Parallel Computing

I am learning about horizontally scaled databases. I hope to implement these ideas soon.

Model Deployment

I implement machine learning models in real world production systems using REST APIs.

Cloud Compute

I maintain DigitalOcean servers for database storage, model training, and model deployment.


Server Management (Linux / SSH) - 3

Database Manipulation (SQL) - 3

Cluster Computing (Spark) - 1

Data Analytics

Visualization and Presentation - 5

Data Munging - 4

Statistical Methods - 3

Machine Learning (AI)

Deep Learning (Keras) - 4

Natural Language Processing - 4

Predictive Modelling (SKLearn) - 4

My Latest Projects

Take a look at my recent work.

Oct 10th, 2018

Scraping 1.4 Million Medium Stories

I recently collected data from 1.4 million stories of

I used the data to make the first public analysis of Medium stories, to create a performance metric to fuel authors, and lastly I published the full dataset for Medium's community of data-scientists.

Sep 16th, 2018

How to Learn Data-Science

In this article, published in Towards Data Science and KDNuggets, I recount my months of self-study and gave advice and resources for the aspiring data-scientist.

This article was the most shared story on KDNuggets for October. It was also well received on, receiving 22k reads since publication and breaking the 99.9th percentile of claps for all Medium articles.

Aug 14th, 2018

Don't Use Dropout in ConvNets

In this project I experimented with regularization in convolutional neural networks. I found that removing dropout layers increased performance in image recognition tasks.

I published an article in Towards Data Science and KDNuggets detailing the experiment and my results.