your complete guide to
machine learning broken down
Join us on an exploration of what machine learning really is. In the following long reads we throw out the jargon, expel the complications, and just present machine learning as it should be. In simple language with metaphors that entertain and enlighten.
Music Log: Stardate 2025.0829
Machine Learning Unplugged: Explained like a rock concert
Our introduction to machine learning, as seen through the lens of a rock concert.
Unpacking machine learning down to the basics, and exploring how it is just one part that makes up artificial intelligence. But the part it plays is one of the most critical in AI’s development.
Captain’s Log: Stardate 2025.0916
Foundation Models: Resistance is futile... to your data
Going beyond the basics ands looking at how machine learning has evolved from it’s first incarnations through to what we have today.
Academic Log: Stardate 2025.0930
Feature Engineering and the Art of Learning
Understand how Machine Learning models learn from the ground up. Explore deeper the essential stages, each one a lesson in how models learn, adapt, and graduate from raw data to intelligent predictions.
Strategist's Log: Stardate 2025.1030
Building Scalable AI: The role of foundation models - Part I
Uncover how, with fine-tuning, you can align machine learning to your business goals, and what you need to do to get maximum impact.
Strategist's Log - Supplemental: Stardate 2025.1113
Building Scalable AI: The role of foundation models - Part II
Uncover how, with fine-tuning, you can align machine learning to your business goals, and what you need to do to get maximum impact.
Curator's Log
How Recommender Systems Shape What We See, Buy, And Love
Recommender systems help companies to predict what users will like based on past behaviours. Read how they are being used across a vast array of industries to influence our online behaviours.
COMING SOON
Curator's Log
How Recommender Systems Shape What We See, Buy, And Love
Recommender systems help companies to predict what users will like based on past behaviours. Read how they are being used across a vast array of industries to influence our online behaviours.
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