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Building Machine Learning and Deep Learning Models on Google Cloud Platform: A Comprehensive Guide for Beginners by Ekaba Bisong

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© Ekaba Bisong 2019
E. . BisongBuilding Machine Learning and Deep Learning Models on Google Cloud Platformhttps://doi.org/10.1007/978-1-4842-4470-8_44

44. Model to Predict the Critical Temperature of Superconductors

Ekaba Bisong1 
(1)
OTTAWA, ON, Canada
 
This chapter builds a regression machine learning model to predict the critical temperature of superconductors. The features for this dataset were derived based on the following superconductor properties:
  • Atomic mass

  • First ionization energy

  • Atomic radius

  • Density

  • Electron affinity

  • Fusion heat

  • Thermal conductivity

  • Valence

And for each property, the mean, weighted mean, geometric mean, weighted geometric mean, entropy, weighted entropy, range, weighted range, standard deviation, and weighted standard deviation ...

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