Data Science

Q-learning, DQN, actor-critic, DDPG, TD3, PPO, SAC and A3C: the update rules, losses, and a full A3C implementation, with what each method fixed.

The state-space model, priors, and Gibbs sampling steps behind CausalImpact, plus how to turn posterior samples into a causal effect estimate.

The Gamma distribution's PDF, its recursive and special-case identities, and how Erlang, Chi-squared, Exponential, Weibull and Poisson derive from it.