Machine learning based predictions of the glass transition temperature $\left(T_\text{g} \right)$, melting temperature $\left(T_\text{m}\right)$, and degradation temperature $\left(T_\text{d}\right)$ for copolymers of two comonomers. Homopolymer predictions are possible by leaving the Comonmer B input field empty. The $2\sigma$ uncertainties are computed using Monte Carlo dropouts.