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This lecture covers the principles of kinetic isotope effects, where isotopes influence reaction kinetics due to differences in mass. It also delves into Linear Free Energy Relationships (LFER), which quantify substituent effects on barrier heights. The discussion includes topics such as ZPE, force constants, and activation energies. Various machine learning methods are introduced, including Decision Trees, Random Forests, and Perceptrons, with chemical examples provided. The lecture emphasizes the application of machine learning in chemistry, particularly in predicting chemical properties and understanding reaction mechanisms.