Notes from Industry

The Endemic Translation Problem found in Data/ML Products

I’ve experienced the growing pains from both sides of the problem — as a Data Scientist and as a Product Manager.

How can you be sure your AI projects succeed? Photo by ThisisEngineering RAEng on Unsplash

The often cited figure (so common in ML/MLOps sales pitches it’s a cliche) is that 85% of AI projects fail to bring their intended results to businesses.

Sloan notes…

A Friendly how-to guide on extracting Garmin Fenix data for people in a hurry

When I started working on a project to analyze my Garmin Fenix data, it wasn’t clear how to access this amazing dataset, and required some technical know-how.

Garmin’s documentation was also hard to follow and outdated, resulting in me having to dig through code repos and old internet forums…

So here is the Garmin Data guide I wish existed when I started this project 🚀

Hopefully…

The fundamental variations between enterprise & consumer product.

During my career, I’ve been blessed to work on products in both a B2B and B2C spaces. Each is exceedingly fun and equally worth pursuing for professional opportunities.

Most Product books are written for B2C applications such as mobile apps. Photo by William Hook on Unsplash

However, I got my very first Product job in B2B. …

Building our own Data Story for Defensive Statistics from Kaggle’s Data Bowl 2021 Data

Understanding the Data Problem: Not All Catches are Created Equal

In American Football, Cornerbacks have the extremely difficult job of preventing Wide Receivers — usually the fastest and tallest players on the field — from catching passes.

As you can imagine, statistics used to measure cornerback performance today include include yards_allowed and completions_per_target , which are widely used to demonstrate…

Continuing our Conversation around Fundamental Human Things that AI fails to replicate

This is a follow-up to my article on 2 Simple Human Tasks That Are Impossible for Today’s AI. Check it out!

Photo by Andy Kelly on Unsplash

With institutions such as OpenAI and DeepMind consistently capturing headlines with their sophisticated AI systems, it seems only inevitable that Machine Intelligence will match (or surpass) Human Intelligence soon.

Exploring tasks that are difficult for Artificial Minds but easy for Biological Ones, and how close we are to bridging the gap

We are living in exciting times.

Artificial Intelligence (AI) seems to be blasting through intellectual barriers previously thought impossible for artificial minds:

  • Playing chess & video games
  • Translating text
  • Diagnosing Patients

and many, many more astonishing achievements.

Photo by Possessed Photography on Unsplash

With all of this recent progress in the field of AI, many people…

How to best prepare for a DS Interview at startups of any round of funding, internships or full time

I’ve spent my career as a Data Scientist at startups. I’ve also been a DS hiring manager for small teams along the way.

People make a lot of mistakes in startup interviews.

Photo by Steve Halama on Unsplash

Today, there is still a huge hiring boom in Data Science — startups are desperate for qualified Data…

How Hedging your Fears can hopefully buy you some piece of mind

**Disclaimer: Politics is inherently a controversial topic, and Politics + Math don’t usually mix well. Please realize this is a casual article, not a treatise on political science…just thought it was fun idea to talk about!**

You don’t need to be following American Politics closely to know that last November’s…

Adam Brownell

Sr. Machine Learning ENG & AI PM || Writing about ML/AI, Product, and the Cognitive Sciences. Love telling Data Stories!

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