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Comet Office Hours: Recap for August 22, 2021

Welcome to another recap of the Comet ML Office Hours, powered by The Artists of Data Science! Let’s jump right in.

Unfortunately, I wasn’t able to attend this past week’s session, but the absence of my questionable ramblings about topics I may or may not fully understand left quite a bit more room for the experts to take the floor.

Reviewing the session, I came across two shorter clips that I found particularly compelling. First, Office Hours regular Mark Freeman brought up a really relatable situation he’s encountering. How do you stay at once learn new skills and areas of expertise while not losing the fundamentals of what you do best?

And second, Harpreet gave an excellent breakdown of how to get the most out of Google Search—a must-know skill for data professionals who consistently need to pull reference information from various sources, file types, and more.

As a reminder, we’d love to see any and all of you at these hourlong sessions—so feel free to register for upcoming Office Hours sessions here!

As always, there’s a lot more in the full session (which you can find on Harpreet’s YouTube channel), so be sure to check it out, alongside all of Harpeet’s other excellent content.


Revisiting the fundamentals

Mark’s question around strategies for relearning fundamentals (in his case, Python) that were once key to your work resonated with me deeply. Without consistent practice and exposure, skills, techniques, and stores of knowledge we once held can seemingly evaporate or be pushed out of our brains by newer inputs.

So how do we stay sharp with the fundamentals that got us to where we are? A few suggestions from the group:

  • Revisit the fundamentals in the most fun way possible: for Harpreet, this included cartoon and Manga flavored books covering subject core to his work
  • Kris, another Office Hours regular, noted that there are generally a couple of reasons why we forget things—we didn’t connect them to other parts of our experience, or they simply weren’t important enough to remember
  • Needing to revisit fundamentals might not be the worst thing—as we grow and gain more experience and context, relearning something in that new context can actually make the relearning process easier and more fulfilling.

 


Harpreet’s Google Search crash course

A question from Office Hours regular Bharat about Python tools and libraries for working with RSS feed data led to an awesome 4-minute tutorial from Harpreet on how to get the most out of Google Search.

I’m admittedly quite lazy and simplistic with my searching, but for data professionals who sometimes need quick, reliable answers and other times need highly-reviewed, comprehensive information about a given topic, knowing how to quickly let Google or other search engines know what you actually want to see is a key skill that’s easily overlooked.

Specifically, Harpreet covered the following tools and processes:

  • Google’s Advanced Search tool
  • How to search in the normal search bar for different file types
  • Using various text string formats to help filter your search
  • How to leverage resources that are adjacent to what you’re looking for to find more relevant content

 


Enjoy the Conversations Above? Join Us!

We run these virtual Office Hours every Sunday at 12pm ET (New York, NY). Completely free to attend and participate, and we’d love to see any and all of you there, help address any questions you might have, and just hang out and talk all things data science and machine learning!

Register for Comet Office Hours


One last thing…

We recently launched The Comet Newsletter, which offers a weekly inside look at all things data science and ML, featuring expert takes and perspective from our team. We have big things planned for both Office Hours and the newsletter, so be sure to subscribe if you haven’t already!

Subscribe to the Comet Newsletter

 

Austin Kodra

Austin Kodra

Austin Kodra is the Head of Community at Comet, where he works with Comet's talented community of Data Scientists and Machine Learners.
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