ML: Li-ion 🔋 Crystal Structure

The video tutorial explores a case study on lithium ion batteries, focusing on predicting crystal structures using feature engineering. It covers various encoding methods, including one-hot encoding, ordinal encoding, and feature hashing, to transform categorical data into numerical data. The tutorial also demonstrates the use of the chem parse package to decompose chemical formulas into elemental counts. The effectiveness of different encoding methods is tested using a decision tree classifier, highlighting the importance of preserving categorical data for accurate predictions.

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