Philosophy Graduate to Machine Learning Practitioner (an interview with Brian Thomas)

Last Updated on August 15, 2020

Getting started in machine learning can be frustrating. There’s so much to learn that it feels overwhelming.

So much so that many developers interested in machine learning never get started. The idea of creating models on ad hoc datasets and entering a Kaggle competition sounds exciting a far off goal.

So how did a Philosophy graduate get started in machine learning?

In this post I interview Brian Thomas.

Brian got started in machine learning using a top-down approach of actually practicing applied machine learning after finding frustration with the theory heavy online courses.

Discover Brian’s story and the the tools and resources he used.

If Brian can find a way to get started in machine learning, so can you.

Q: What resources have you already tried to understand machine learning?

What works:

Your Jump-Start Scikit-Learn and Jump-Start Machine Learning in R were very valuable early on as maps of the
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