If you’ve been on or near the Generative AI (Gen AI) rollercoaster that has characterised the last year or so, it is likely you will have come across the acronym ‘RAG’. RAG stands for ‘Retrieval-Augmented Generation’. It is an approach commonly credited to a 2021 paper by a team
Personal
Inspired by Chip Huyen's similarly titled post, this post summarises some of my thoughts on why joining a startup might just be the best decision you could make for your career, and a word of caution for those considering doing just that.
Engineering Skills for Data Scientists
Deploying a Machine Learning (ML) model as a live service to be consumed by a business-critical system or directly by end-users can be a scary prospect. This post looks at how you can perform load testing on your model APIs to ensure they can stand up to even the highest-demand situations.
Programming
Flask is a popular 'micro-framework' for building web APIs in Python. However, getting a Flask API 'into production' can be a little tricky for newcomers. This post provides a minimal template project for a Flask API, and gives some tips on how to build out basic production Flask APIs.
Personal
A rundown of my 5 favourite books from 2020, with a few honourable mentions to boot.
Data Science
This article analyses 30,000 unique Data Science blog posts from the last year to get to the bottom of what the Data Science community has been discussing. This post looks at the most discussed -- and most popular -- technologies of the year.
Engineering Skills for Data Scientists
Data models and data formats are an easily overlooked but critical aspect of modern data infrastructure and development work. This post gives an introduction to HDF5 and how to get started using it in Go.
Computer Science Fundamentals
In Part 1 of this mini-series, you saw how OOP concepts can be used to structure and manipulate code. In this part, you'll see how these ideas are formally defined, and look at a couple of more advanced concepts too.
Data Science
Xanthus is a Deep Learning (DL) library built on top of Tensorflow and uses the Keras API to implement various neural recommendation model architectures. This post benchmarks the models implemented in Xanthus against some popular 'classic' matrix factorisation models.
Technology
Streamlit is a minimal, modern data visualization framework that's rapidly becoming the go-to dataapp framework in the Python ecosystem. This post introduces Streamlit, and shows you how to securely and scalably deploy your Streamlit apps with Google App Engine.
Computer Science Fundamentals
Whether you're a fan or not, OOP is a valuable tool in your programming toolkit. It's also sometimes a little bewildering for new programmers (and some more experienced ones too). This post provides a (brief) practical introduction to OOP concepts.
Engineering Skills for Data Scientists
MLOps is an emerging engineering movement aimed at accelerating the delivery of reliable, working ML software on an ongoing basis. This post provides an intro to MLOps and gives you an example project to get you started with building your own ML pipelines using GitHub Actions and Google Cloud.
Engineering Skills for Data Scientists
Deploying ML models 'into production' as scalable APIs can be tricky. This post looks at how Serverless Functions can make deployment easier for some applications, and gives an example project to get you started deploying your own models as Google Cloud Functions.
Engineering Skills for Data Scientists
This post introduces the concepts behind 'serverless computing' -- a way of quickly and easily deploying lightweight apps (e.g. APIs). It looks at the associated advantages and disadvantages of serverless, and gives a short example showing how to deploy your own serverless function to Google Cloud.
Artificial Intelligence
This post introduces Xanthus - a new open source Deep Learning package built on TensorFlow 2.0 for quickly and easily building state of the art recommendation models in Python.
Literature
It's easy to feel that the present times are 'unprecedented'. Yet sometimes it's clear that the events of today are echoes of problems familiar to those in the past. This post shares an essay written by Orwell in 1945, that feels particularly relevant to the times.