Unbundling of people or ‘rise of the creator class’ If you work in Tech you end up exposed to trends, and if you’re a product-focused engineer you think a lot about ‘product’, product strategy and what’s ‘coming next’. One question in our current ecosystem is ‘what’s next after marketplaces’ we’ve already seen very successful companies… Continue reading The rise of the creator class
One of the distinctions I like to make about modern ‘Data Science’ is between ‘data science for decision support’ and ‘machine learning’. h Basically speaking machine learning, which is often product-focused – is generally something like ‘there’s this problem in fraud, credit scoring’ and we need an automated and deployed system. You’ll often work super… Continue reading Data Science for Decision Support: Or why Bayesian Analysis matters
I’ve been working on software products for several years now. And while a lot of my work has been greenfield, I’ve struggled to articulate the different kinds of work that happens in product development. Des Traynor one of the founders of Intercom had a great talk about this. (Source: Video) Often people don’t understand the two… Continue reading The two kinds of work in Software Products
Some lessons learned from React Native Development I’ve recently been writing some react native so I wanted to enumerate an opinionated list of things I’ve learned. I’d not done any mobile development before this, so consider this a reasonable approximation of how an experienced engineer would get their heads around that ecosystem. Use SDK/ Managed Services… Continue reading 4 Lessons learned from React Native development
I recently wrote an email to an Irish Entrepreneur about the challenges of using Kubernetes and Kafka. I think both technologies are awesome, but I’ve seen in the past companies trying to integrate them without thinking about the managed services that exist out there. Kubernetes If you’re doing it yourself I’d look at https://docs.aws.amazon.com/eks/latest/userguide/getting-started.html which is from… Continue reading Why serverless matters or how do you want to spend your innovation tokens?
I recently caught up with Noelle Saldana and she shared some of her experiences as a Data Scientist and Product Management expert. She’s got a strong technical background and has worked for Pivotal a leading technology consultancy helping Forbes 500 learn how to leverage Machine Learning. She’s recently joined Salesforce where she’ll be wearing a… Continue reading “Much of our day-to-day lives are touched and improved by Data”
I’ve got an online course called Probabilistic Programming Primer You may be wondering what that’s all about, so I put together a video explainer all about it. Building easy to interpret models isn’t a nice to have anymore it is the reason people pay for models in the first place. And as we see more… Continue reading Introduction to Probabilistic Programming Primer
I recently put together a survey of over 100 data scientists and analysts. There’ll be a report coming super soon, but before then I wanted to share the infographic. We’ll go into more detail in the report. If you’d like to get access to the report you should sign up here 70 percent of data scientists… Continue reading State of PPL: How are Bayesian methods used in industry?
(Reprint from a few years ago) Cameron is an open source contributor, a pythonista and a data geek – he’s developed various cool libraries. His blog is worth a read, and I personally recommend his screencasts. He’s got a strong Mathematical background like myself, and he currently is Lead Data Analyst in a Data Science job… Continue reading Interview with a Data Scientist – Cameron Davidson Pilon
(Reprint from last year) I interviewed the interesting and fascinating Ian Wong – he’s the technical co-founder of OpenDoor, which I personally think is amazing as a concept! 1. What project have you worked on do you wish you could go back to, and do better? Pretty much any project I’ve worked on in the… Continue reading Interview with a Data Scientist – Ian Wong Open Door