The Biggest Challenge in Data Science
By this point, data science seems ubiquitous and wildly successful. Recommendation engines govern the content...
5 Data Trends to Watch in 2018
Along with a New Year come predictions for what’s hot and what’s not. Here’s five...
5 Data Science Trends that Need to End
If you’ve taken an introductory course in data science, or simply read a lot of...
Does My Model Smell Funny? Top Takeaways from Technical Debt in Machine Learning Systems
Sniffing Out Technical Debt in Machine Learning Solutions With the democratization and open-sourcing of machine...
3 Key Architecture Takeaways from DAS 2017
I recently attended the 2017 Data Architecture Summit hosted by DATAVERSITY in Chicago. The audience,...
Demystifying Neural Networks: the Theory
In my previous post on the Deep Learning Summit in Boston, I discussed Maithra Raghu’s...
Highlights from the Deep Learning Summit: Neural Networks Demystified and Domain Adaptation
I recently had the pleasure of attending REWORK’s Deep Learning Summit in Boston. Two topics...
Deep Learning: Its Power, Promise and the Future of Analytics
Artificial intelligence (AI) won’t be taking over our world, but it will be augmenting human...
Which One to Choose? Comparing Machine Learning Techniques
Machine learning’s utility in the commercial landscape has been firmly established, and its popularity is...
Teaching Machines: What is Machine Learning?
Data Science and machine learning have generated a lot of discussion surrounding them in the...
7 Trends in Analytics for 2017
What’s new and exciting in the world of analytics for 2017? Here’s our list of...
Full Stack Data Science in Two Weeks: A Painful Retrospective
In the wake of the announcement that the city of Washington, DC would receive its...