What is the name of the Python library developed by Google for deep learning?

The correct answer is Keras, a high-level Python library developed by Google that facilitates building and training deep learning models. Keras was designed to be user-friendly and modular, enabling developers to easily create neural networks by abstracting away many of the complexities associated with directly working with lower-level machine learning frameworks.

While Keras initially served as a wrapper for the TensorFlow library, its integration into TensorFlow as the default high-level API reinforces its prominence within the deep learning community. This makes it particularly accessible for those new to deep learning, while still giving advanced users the flexibility to customize their models deeply.

The other options listed represent different deep learning libraries but have distinct origins and functionalities. Caffe, for instance, was developed by the Berkeley Vision and Learning Center and is known for its speed but is less user-friendly compared to Keras. Theano, meanwhile, was one of the first libraries for numerical computation that enabled efficient deep learning but is no longer actively maintained, making it less relevant in the current ecosystem. PyTorch, developed by Facebook, is another popular library but emphasizes a different workflow and programming style, making it separate from Keras in terms of development and community usage.