Detrending Seasonal Data
A quick Python Notebook to show you how to use statsmodels to detrend seasonal data.
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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 min
Overfitting and Underfitting
What is meant by a complex model? What does overfitting mean? All these questions are answered in this intuitive Python workshop.
Support Vector Machines
A python notebook demonstrating the use of support vector machines.
Logistic Regression
Logistic regression is very useful for producing probability estimates for classification. This simple workshop shows you how.
Linear Classification
We can also use linear models for classification purposes. Find out how in this workshop.
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