I’m going to use a bit of a click bait title for this article. But the aim of this article is to share experiences I’ve gathered from about 10 years building ML systems, and building ML teams. Why ML is about more than ML I saw the following tweets by Erik so I’ve added them.… Continue reading Why building ML systems is about more than ML?
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”
Learning to use the Cloud A common question from a Developer or a student is ‘how do I learn AWS or GCP’. For those of you who don’t know AWS – stands for Amazon Web Services and GCP stands for Google Cloud Platform. At the current moment in time I’ve no opinions on Azure from… Continue reading I’m lost, how do I learn to use the Cloud?
I’ve been contributing on and off to PyMC3 and other projects for a few years now. I’m still learning a lot about Bayesian Statistics and building software. I intend to continue to work on this stuff. Chris Fonnesbeck – recently did a talk at NeurIPS where he talks about some of the stuff we’ve learned in… Continue reading 3 key lessons from being an OSS developer
I’ve been recently playing around with ‘arviz’. For those of you who don’t know Arviz is a library for exploratory analysis Bayesian Models. I’ve got a Bayesian model built – or someone has built one for me, how do I explore it? How do I plot it? This is the fundamental question that Arviz answers.… Continue reading How do I visualise the results of a Bayesian Model: Rugby models in Arviz
Inspired by Vicki I decided to build a Tweetbot – the code is available here. You can follow the tweetbot online – the architecture that Vicki proposed is basically what I did, only I made a few changes in the code. Time taken It’s worth pointing out first that it took me approximately 32 hours of… Continue reading How to use AWS Lambda to build a tweetbot
The insightful Data Scientist Trey Causey talks about Software Development Skills for Data Scientists I’m going to write about my views on Code Review – as a Data Scientist with a few years experience, and experience delivering Data Products at organizations of varying sizes. I’m not perfect and I’m still maturing as an Engineer. A good… Continue reading Why Code review? Or why should I care as a data scientist.
I interviewed one of the core members of the Pandas Python Library Masaaki Horikoshi (sinhrks). I was really happy to interview him, and glad to show that Data-science and software development are really global things 🙂 I lightly edited his answers at his request because English is not his native language. My Biography: I work as… Continue reading Interview with a Data Scientist Tool Developer