PyMC3 is a Python library for probabilistic programming, enabling the creation of Bayesian statistical models. It allows users to define models using a high-level syntax, which can then be used to infer parameters from data using powerful sampling techniques like Markov Chain Monte Carlo (MCMC). PyMC3 is widely used in machine learning, finance, and scientific research, where uncertainty and probabilistic reasoning are essential. Its flexibility makes it suitable for complex models, and it integrates well with other Python libraries like NumPy and TensorFlow. PyMC3's ability to provide uncertainty estimates for predictions sets it apart from traditional machine learning methods.