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

© 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 ...