A K-means algorithm for the detection of false banknotes

Gustavo Mangold

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ML Engineer

Graduate Student

Software Engineer

Python

scikit-learn

TensorFlow

Using the scikitlearn library, we generate, by recursive feeding of the k-means algorithm, a graph that classifies the banknotes in two clusters. The blue cluster is composed of the real notes and the orange one composes the false notes. With a reading of some new note, we can then binarily classify the note into false or real. The algorithm is unsupervised.
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Using the scikitlearn library, we generate, by recursive feeding of the k-means algorithm, a graph that classifies the banknotes in two clusters.

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ML Engineer

Graduate Student

Software Engineer

Python

scikit-learn

TensorFlow

Gustavo Mangold

Problem-solving ML and software engineer

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