Getting Started with Machine Learning Monitoring
Machine learning models are powerful tools when used to automate processes and inform data-led decisions. But the effectiveness of models can degrade if […]
Explainability in Machine Learning
Machine learning is becoming an integral part in how the modern world functions. The collection of data has increased exponentially alongside advances in […]
Bias vs Fairness vs Explainability in AI
Over the last few years, there has been a distinct focus on building machine learning systems that are, in some way, responsible […]
What is MLOps?
I recently started a new job at a Machine Learning startup. I’ve given up trying to explain what I do to non-technical […]
Drift Detection: An Introduction
What is Drift Detection? Deployed machine learning models can fail spectacularly in response to seemingly benign changes to the underlying process being […]
Machine Learning in Finance
The financial and banking sectors are incredibly data-rich, with millions of transactions and transfers occurring every day. Data-led decisions are an integral […]
What is Covariate Shift?
Covariate shift is a specific type of dataset shift often encountered in machine learning. It is when the distribution of input data shifts […]
A/B Testing for Machine Learning
A/B testing is an optimisation technique often used to understand how an altered variable affects audience or user engagement. It’s a common […]
What is Cross Validation in Machine Learning
Cross validation is the use of various techniques to evaluate a machine learning model’s ability to generalise when processing new and unseen datasets. […]
Machine Learning Optimization – Why is it so Important?
The concept of optimisation is integral to machine learning. Most machine learning models use training data to learn the relationship between input […]
What is Deep Learning?
Deep learning is a form of machine learning which aims to mimic and imitate the processes of the human brain through machine learning […]
Outlier Detection and Analysis Methods
Outlier detection is a key consideration within the development and deployment of machine learning algorithms. Models are often developed and leveraged to […]