Finding the biggest and best Tech Meetups in the Bay Area

Answering the call

Just a few days ago my friend Johannes Giorgis introduced a new feature series, Data Science Challenges (DSC). DSC will provide new challenges every two weeks that will motivate you to:

  1. build your software engineering skills
  2. introduce new ways of thinking about problems using data science
  3. give you fresh ideas for your portfolio

These open-format challenges provide guidance and boundaries to narrow the scope of your work, giving you a project small enough to finish in a few hours, but big enough to challenge your skills and maybe let…


We wanted something fun and original for the new logo that would look fantastic both online and in print. After talking to friends, trying to make my own, and never even getting close, I finally found a design firm in Bangkok that could give me exactly what we needed.

Jack, the red panda

It took a few drafts but ultimately we landed on Jack, and I think the results are pretty spectacular; I am so glad I hired a professional.


Last year, I wanted to find a good way to visually demonstrate a way to paint a boolean matrix. Great visualizations make all the difference when it comes to explaining how things work, so I used MatPlotLib, an excellent Python library to show one way to paint a Boolean Matrix.

Pastel Ball Python Snake watercolor by Slaveika Aaladjova
Painting with Python and MatplotLib


Jupyter notebooks are great, but Google Colaboratory (Colab) takes the next level. Colab gives you notebooks that link to the rest of Google’s infrastructure, giving you access to Google’s infrastructure such as their GPUs, TPUs, and Google Drive. This is fantastic, especially if you have large data sets or you want access to a high-end GPU, or TPU.

Back in October of 2018, I wrote a step-by-step guide, in Google Colab, that shows you how to marry Drive data to your Colab Notebooks. If you like Jupyter, you’re going to love Colaboratory.


Back in August 2018, Anna, Andrei, and I worked together to build Deep Red, a dedicated machine learning workstation.

It’s absolutely beautiful, lightning fast, and capable of training two neural networks at once, each on a dedicated GeForce GTX 1080 Ti.

For more information, take a look at the parts list above.

Andrew Key

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