The podcast you’re about to hear is one of a handful of interviews I recorded live from the O’Reilly AI and Strata conferences in New York City.

This time, I interview Diogo Almeida, senior data scientist at healthcare startup Enlitic. Diogo’s presentation at the conference focused on in-the-trenches deep learning, and was titled “Deep Learning: Modular in theory, inflexible in practice.”

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In the interview, Diogo and I discuss the ideas he presented, which are centered on the data, software, optimization and understanding issues surrounding deep learning. Diogo is also a past 1st place Kaggle competition winner, and we also spend some time discussing the competition he competed in and the approach he took lisinopril 10 mg tablet.

A bit of a listener warning: Our conversation gets pretty technical pretty quickly. I try to make sure to summarize key points from time to time, and if you hang in there I’m sure you’ll learn a lot. Let me know how you like this level of detail.

Also, as is the case with my other field recordings, there’s a bit of unavoidable background noise. Sorry for that.

About Diogo Almeida

• Diogo Almeida on LinkedIn
• Diogo’s GitHub Profile
• Me vs NP

Mentioned in the Interview

• The Cause-Effect Pairs Challenge on Kaggle
• Diogo’s Presentation at the O’Reilly AI Conference
• What is the VC dimension of a Neural Network?
• Penn Treebank Project
• MNIST dataset
• CIFAR-10 and CIFAR-100 datasets
• ImageNet dataset
• “Inception” paper
• “ResNets” paper