3D text attribute control in A-Frame

Here’s a 3D thing I made that changes the color of the text when its respective cube is selected – check it out! If you’re not familiar with A-Frame, it’s a javascript language built on top of three.js (which itself is an abstraction of WebGL) that lets you quickly create 3D scenes in HTML. It even supports VR mode so that you can view objects on a VR device – like Google Cardboard, Vive or Oculus. In the new master version of A-Frame, 0.5.0, you can add text like I did here and do stuff with it!

Interactive PCA Scatterplots

This is an HTML interactive plot of the popular iris dataset that is compatible with Jupyter Notebook. When the paintbrush is selected, it allows you to select a subset of data to be highlighted among all of the plots. When the cross-arrow is selected, it allows you to to mouseover the data point and see information about the original data. This functionality is very useful when doing exploratory data analysis.

Here is the code:

Teaching and Tutoring

So, I’m back in good ol’ Chicago. This Fall I am teaching Physical Science at Harold Washington College. This weekend I am hosting a Python for Data Science workshop at General Assembly. I am also trying to set myself for my next gig in data science. Some people who secretly read this blog may have given me a loan to attend the Galvanize Data Science Immersive. If that’s you, thank you and I do not want to disappoint you! If not, thanks for reading this blog for whatever reason. Another thing I’m doing on the side is tutoring – which is like very short term consulting for education! So the common theme is that I’m teaching a bunch of stuff. And that it all has math and/or statistics in it – gotta love that stuff!

Consulting – Soft Launch!

I would like to announce a (very) soft launch of new services that I am offering for consulting. Take a look at my consulting page on this site for more info!

I am for hire! I am looking for new clients. Since I am the new kid in school, expect super competitive rates! I am familiar with data science and engineering type problems (sensors, energy, etc.), but would be open to anything that can be solved analytically! Let’s talk!


You or your company may have a problem that you do not having the time or expertise to look into yourselves. If that’s the case, maybe I could help!

Here’s a taste of services I would be very comfortable offering:

  • Estimate solar power and cost of solar panel installation on your building
  • Design wireless sensors for real-time measurements
  • An Internet of Things (IoT) application
  • Design a web or Android app for remote control
  • Design a part to be 3D printed
  • Design an Arduino or soldering class
  • Anything else! Possibly: image recognition, finding important variables, electronics analysis. Take a look at my about page for other services I may be able to provide and how to contact me.

Capstone project update

Getting Satellite Data

In short, getting satellite data from the government is a big headache. The trouble includes links that loop you around to the original site, multiple sites for a given satellite/project, weird registration for data access, and verbose and obscure variable names. I guess this is part of being a data scientist.

Research from NREL on the topic

These slides include a list of resources of satellites with cloud information. When I’m done downloading the data, I will do cloud computing in the clouds on the clouds!

(Big) Data Science Happenings

Big Data! Cloud Computing!

So, I’ve been learning quite a bit at Galvanize this past week about Spark and AWS. Today it culminated in deploying Spark on multiple clusters on AWS to process large files. Spark has a growing number of machine learning models available, so you can do machine learning in the cloud!

Earlier this week I deployed a small AWS instance and installed Anaconda on it. When running IPython Notebook from AWS, I used a password to protect it. It’s really freaking cool that you can remotely access IPython Notebook! The only problem that I had was that matplotlib didn’t display plots. This was solved by installing the ubuntu-desktop which loaded the qt backend necessary for matplotlib to make plots.

Capstone Project!

I’ve really got to start buckling down on this capstone project. Thanks to Galvanize instructors Isaac and Clayton for bouncing ideas today!

Capstone project

I just finished my fourth week at Zipfian Academy (Galvanize data science immersive) and I’ve been learning a lot about machine learning algorithms such as random forests, boosting, and support vector machines that are used in data classification. I looked at some Python code again that I was trying to figure out a few months ago that employed machine learning and I understood it better. Practice makes perfect they say. And there’s no shortage of practice at Zipfian!

While the exercises can be instructive, I learn the most when working on projects. And the biggest project at Zipfian is our capstone project. We have a month to work on a dataset (or datasets) for a specific subject. Currently, I have several ideas for my project. I had been working on EEG data before Zipfian, so the analysis uses machine learning but it is not really in the same spirit of “web scraping social data to find interesting insights” demonstration of data science flexing its muscles.

I come from a solar energy background, so it would be interesting to do a project looking at solar panel failure rate and find contributing factors. Given that food shortage is a current and future worldwide issue, I would like to look improve the efficiency of a vertical farm – an indoor, completely controlled environment for farming – by analyzing data collected by sensors such as light level, water level, pH, electricity usage, air flow, etc. This, I believe, would be very interesting and relevant as California continues to experience water shortage. However, there may not be enough information on this yet, so I may have to use data for regular old outside data. I’ll keep you posted as I hone in on a project idea. Leave a comment if you have an idea or have a lead for an interesting dataset!