Keras is a Python library for deep learning. Deep learning is a sub-branch of artificial intelligence that focuses on solving complex computations by emulating the working process of a human brain. Neural networks, computational graphs composed of nodes representing multiple operators for breaking down the tasks into smaller parts for faster computation, are used for solving many of these problems. However, they are difficult to implement, and using the Keras library makes this task much easier. This Keras guide will cover this and more. Keras is highly recommended for beginners due to its minimalistic and modular approach.

PyTorch is an open-source framework built for developing machine learning and deep learning models. In particular, this framework provides the stability and support required for building computational models in the development phase and deploying them in the production phase. PyTorch functionalities are extensible with other Python libraries like NumPy and SciPy. Additionally, the strong GPU acceleration of PyTorch enables it to perform high-level tensor computations with ease. It's also used with TorchScript, which is a built-in tool that makes PyTorch flexible while seamlessly transitioning between eager execution mode and graph mode to achieve higher speed and optimization.