Related Posts
Ladies, take note: Corona pick up lines are here.
Additional Posts in Data & Analytics Consultants
New to Fishbowl?
Download the Fishbowl app to
unlock all discussions on Fishbowl.
unlock all discussions on Fishbowl.
Ladies, take note: Corona pick up lines are here.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Download the Fishbowl app to unlock all discussions on Fishbowl.
Copy and paste embed code on your site
Send download link to your phone
OR
Scan your QR code to download
Fishbowl app on your mobile
1. Have a repo with non-usual suspects datasets. Think beyond Iris, Titanic, MNIST ...
2. Have projects where you can in whole or in part talk about end to end life cycle steps. Try cleansing Zillow or Mueller. Or ingest Panama Papers.
3. Think beyond just training a model. Show how you can deploy the models as served endpoints. Show how you have built a continuous training loop.
4. Showcase how the models can be turned into microservices and be secured.
5. Incorporate bias detection and explainability into the work, however simple and trivial they maybe.
6. Feature tuning, model metrics dissection, data summarization, .... understanding these darn well is table stakes.
Don’t get too hung up on just learning the algorithms. They are essential, but there is a lot more.
GitHub projects/software dev > certs for data science
Yeah you'll get schooled if you put yourself out there as a DS and go through a technical interview (when all you've done is a Coursera class or two). Be up front with your knowledge and skills. If you have the basics down, just say it before the interviewers ask you to explain gradient descent 😉
So, if someone asks technical questions to gauge the fit, he is trying to prove that he is smarter. What a logic! 😂