DataGig

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Our founder would be speaking at the RE.WORK Applied AI Summit. Hear the presentation on “The digital apprenticeship marketplace for the next generation of data professionals” on November 29-30 in Houston.
The summit is a unique opportunity to hear the latest advancements in AI and how it’s being applied in many Industries.
If you’ve been following her or DataGig, you know our mission is to empower one million data scientists and make a contribution towards the advancement of new AI technologies.
If you’ll like to learn more about our new apprenticeship program, send over a private message. :)
If you’d like to attend the summit, use code SP2018 for 20% off your pass here: https://bit.ly/2CFTE4K
Hope to see you there!! .

I’ll post about my experiences in data science & machine learning & I’m often asked for a case study. I am the case study. If you’re in the field using anything other than regression, random forests, Bayesian methods, etc., you are the case study too.
We often forget how young our field is. There are firsts happening every day. Many companies are now working with data science, but few have gone beyond basic approaches. Fewer have built a repeatable process for getting them into production. If you’ve done either of those things, you are the case study.
When Cassie Kozyrkov talks about building AI based systems, she is the case study. When you build a deep learning model that outperforms traditional approaches, your work is the case study.
The knowledge we share with each other is so important. We’re each learning in our own way from experience. Spread what you’ve learned. Even if you called it a failure, you’ll prevent others from going down the same path.

The easiest way to pick a fight with a data scientist is to make fun of their chosen tools & programming language. If I called out R or python for any number of legitimate flaws, I'd get hate mail for weeks. Our dedication to them is more faith than fact based so our responses are more fanatical than rational.
You can get most data scientists to agree that each tool has its uses & flaws. If you say python is bad for this or R is poorly suited to that, an army rises to their defense.
You are not defined by your tools or programming languages. Their flaws are not yours. Expand your skills by learning new ones. Admit where your chosen set is right & wrong for the job. Don’t worry about defending your chosen tools & languages. Their capabilities can defend themselves.
Most of all don't cling to them when they are obviously ill suited to the task. I've cleaned up enough messes caused by, "That's just what we've always used."