Quantitative Model Evaluation
To be able to create models, you need to know how to compare them. In this python notebook you will learn how to compare models quantitatively. I.e. create summary statistics for your model's performance.
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Qualitative Model Evaluation - Visualising Performance
You should always try and visualise your data science. Especially when measuring model performance because this allows you to easily compare and spot errors with models. This Python Notebook shows you visualise model performance.
Hierarchical Clustering - Agglomerative
Often data is produced by a process that has some natural hierarchy. If you have a clustering problem where this is true, hierarchical clustering works really well. Find out more in this Python Notebook.
Evidence, Probabilities and Naive Bayes
Probabilistic models are great at promoting good science. I.e. we're trying to model features to predict outputs. In this Python Notebook you will learn how to calculate bayes rule and use a naive bayes classifier.
Detrending Seasonal Data
A quick Python Notebook to show you how to use statsmodels to detrend seasonal data.
Visualising Underfitting and Overfitting in High Dimensional Data
Most of the time you have too many dimensions to simply plot the decision boundary of a classifier. This workshop investigates other ways to visualise under and overfitting in high-dimensional datasets.
Nearest Neighbour Algorithms
Nearest neighbour algorithms are useful for all kinds of problems. This python notebook explains what it is and how to use it.
K-NN For Classification
We can use the nearest neighbour algorithm for classification too. This python notebook explains how to perform the k-Nearest Neighbours algorithm.
Introduction to Monitoring Microservices with Prometheus
Learn how to monitor microservices with Prometheus. Expert-led introduction from Phil Winder.
Dr. Phil Winder
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7 minLogging vs Tracing vs Monitoring
Monitoring != Logging != Tracing. Learn the differences between these three fundamental cloud-native concepts. Find out the uses cases for each technology.
Dr. Phil Winder
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2 minNewsletter
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