There Are Many Roads to Machine Learning

You cannot abandon your path, and nor should you

My only hard-and-fast rule: don’t have any hard-and-fast rules.

When I started in machine learning ten years ago, my head was spinning with all the hard-and-fast rules shouted at me by the industry thought leaders and influencers, most of them starting with the phrase “you can’t.”

“You can’t do machine learning without a PhD.”

“You can’t do machine learning without math.”

“You can’t do machine learning without TensorFlow.”

“You can’t do machine learning without SQL.”

Over the past ten years, as my experience grew and the field matured into a wildly interdisciplinary branch of science and engineering, I have found that none of the often-echoed statements are true.

There are multiple roads to machine learning, and none of them are superior.