Machine Learning for environmental data

Use machine learning tools designed to allow non-experts to use advanced methods as responsibly as possible.

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ML

Uncertainty and Variability in Geology

Another technical note in the Art of Science series by Dan Cornford of IGI Ltd. Uncertainty and variability are often confused. The former represents a state of our minds, the later a state of nature.

Dan Cornford

Managing Director​

ML

The extinction of machine learning?

A short note by Dan Cornford on the place of machine learning in the geosciences, part of the Art of Science series of technical notes. Please click here to read the full technical note: 

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Dan Cornford

Managing Director​

Key features

Tools to help you explore, explain and predict.

Use a series of data pre-processing steps to ensure your data is ready for machine learning modelling. This includes extreme value and outlier removal, dimension reduction, scaling of data and the treatment of missing values.

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Select from a range of clustering models to group your data, or regression and classification models to predict values for continuous and discrete variables. 

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Use a range of diagnostic plots to understand the performance of your models and select an appropriate model for your problem. Use computational methods to automatically explore a range of model structures.

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Explore your models in detail to examine the impact of each input variable, and understand why certain groupings occur when clustering.

FeatureImportanceWATR

The machine learning tools are in continuous development. Check the latest news to find out the latest features. Our aim is to provide advanced tools that can be used safely without needing to be a machine learning expert. Building on our deep understanding of statistics and machine learning you won't need to ask an AI - we've built the tools to help you make good choices!

Contact us to find out about our machine learning tools