Keeping Up With Data — Week 19 Reading List

5 minutes for 5 hours’ worth of reading

Adam Votava
2 min readMay 14, 2021

This week has been full of challenges. How to forecast demand in the post-covid times? How to automate quality control in increasingly complex manufacturing processes? How to compel front-line workers with the power of data? I wish I were a ‘multiprocessor’ like Bill Gates!

You won’t be surprised that this week’s articles are tilted towards the questions posed above.

  • Greykite: A flexible, intuitive, and fast forecasting library: Forecasting has never been easy. And covid hasn’t made it easier. Now, LinkedIn is making its Python library for forecasting available. It claims to be very flexible, intuitive, and fast. Flexibility is very important. During the uncertain times of post-covid world, data scientists will need to make use of many other data rather than only using the historical time series. (LinkedIn Engineering)
  • Algorithm-Assisted Inventory Curation: What items to add to the inventory in the fashion industry? And how can data and analytics help with that? The team at Stich Fix describes their approach to answering these questions. I’m a big fan of the team as they are not only thinking business first (see how they approach the features or the evaluation of the analytical solution) but they are also sharing it with the community. (Stitch Fix)
  • Data Apps and the Natural Maturation of AI: Technology is not disrupting businesses; how it’s being used by companies is. AI — as a technology — has great potential but not every company has the budget and capacity to leverage it. And so, enter data apps: “a category of domain-infused, AI-powered apps designed to help non-technical users manage data-intensive operations to achieve specific business outcomes.” These data apps must be designed around the needs and behaviours of its users. It is the responsibility of the vendors to do that. It’s not up to the users to figure out how and what to do with these apps. Quite a big philosophical shift, isn’t it? (Data Science Central)

I’m in Prague for the weekend and so will see some friends and family in person — for the first time in several months! So, I have an extra reason to look forward to the weekend.

In case you missed the last week’s issue of Keeping up with data

Thanks for reading!

Please feel free to share your thoughts or reading tips in the comments.

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Adam Votava

Data scientist | avid cyclist | amateur pianist (I'm sharing my personal opinion and experience, which should not to be considered professional advice)