Dive into Deep Reinforcement Learning: Understand how AI learns from mistakes to improve decisions in complex environments. Perfect for tech enthusiasts and professionals.

Deep learning is a branch of artificial intelligence that deals with the simulation of human intelligence by machines.

A Variational Autoencoder (VAE) is a type of artificial neural network used in the field of machine learning for the purpose of generating new data.

Machine learning is a subset of artificial intelligence (AI) that enables computers to learn from experience and improve over time.

Supervised learning is a type of machine learning algorithm that involves learning from a set of training data that has been labeled with the correct answers.

Reinforcement learning is a subfield of machine learning, concerned with how software agents can learn to behave in complex, uncertain environments. It relies on feedback from the environment in order to improve the agent's behavior.

A large language model is an artificial intelligence system that has been trained on a massive amount of text data, using machine learning algorithms, to generate human-like responses to text-based inputs.

Data science is the study of extracting knowledge and insights from data.

Linear algebra is the study of mathematical problems that can be best explained in terms of lines and linear equations.