RESOURCES WE LOVE
Cut through the hype with this curated collection of Valkyrie-recommended articles, resources and thought leaders to help you navigate the burgeoning field of data science.
RESOURCES
Why we love it:
Medium
RAPIDS cuGraph
Ben Jack
Another fascinating application of graph theory
Why we love it:
Nature Medicine
Designing neural networks through neuroevolution
Ben Jack
If we ever get to AGI, I think it will be evolved from the bottom up, not designed from the top down...
Why we love it
MultiThreaded
Beware the data science pin factory: The power of the full-stack data science generalist and the perils of division of labor through function
Ben Jack
In defense of data science generalists...
Why we love it:
Cornell University
Learning Discrete Structures for Graph Neural Networks
Charlie Burgoyne
Advancements in ML over the next 10 years will be dependent on the advancement of GNNs
Why we love it:
Quanta Magazine
A New Approach to Understanding How Machines Think
Meredith Butterfield
Fascinating exploration of work on interpretability and trust in AI.
Why we love it
Coursera
AI For Everyone
Ben Jack
New AI course from Andrew Ng!
Why we love it:
Independent Contributor
Understanding LSTM Networks
Charlie Burgoyne
An elegant introduction to RNNs and a common application
Why we love it:
The Launchpad
Your Deep-Learning-Tools-for-Enterprises Startup Will Fail
Ben Jack
This article makes a clear case for why productizing data science services is challenging.
Why we love it:
DataFramed
The Credibility Crisis in Data Science (with Skipper Seabold)
Ben Jack
Great recent podcast episode on a critical challenge we should all be thinking about.
