Keras
Keras is a high-level deep learning API meant to be very user-friendly and so that the code would also be very interchangeable among the different systems. It was born within the group of the projects referred to as the TensorFlow but can also work in the conjunction with the Microsoft Cognitive Toolkit (CNTK). It was built in expectation to feedback and to iterate so quickly that as the new approaches to the solving deep learning problems emerge. On the one hand, Keras is simple and easy-to-use for everyone including non-professionals, but it serves also the experienced people providing the sufficient tools for them on the other hand. Its building blocks architecture is much like Legos, it is not only customizable but also could be extended.
Key Features:
- Keras provides a usual interface which is utilized for the creating the neural networks. Therefore, both beginners and also the experienced developers may conveniently start a project.
- It is based on the principle of modularity, which makes adding and updating the features much more simple and also convenient.
- Modular codes in Keras make it a very easy-to-use neural network library of TensorFlow especially when they are used in the prototyping.
Pros:
- User friendliness, ergonomics, that even a non-experienced user can handle it.
- Assessment by playwright. For advanced users, they can build upon the premise created by the playwright.
- Integration cross different states like TensorFlow and also other frameworks without any difficulty.
Cons:
- They might not have the level of functionality found in TensorFlow and in PyTorch, as the latter are much more advanced.
- The restrictedness of the upper frameworks compared to the lower ones.
Keras vs Tensorflow vs Pytorch
One of the key roles played by deep learning frameworks for the implementations of the machine learning models is the constructing and deploying of the models. They are the components that empower the artificial intelligence systems in terms of learning, the memory establishment and also implementation. In this article, we’ll see three prominent deep learning frameworks: TensorFlow, PyTorch and also Keras are founded by Google, Facebook, and also Python respectively and they are quite widely used among the researchers and also the practitioners. In general, frameworks like these are created very differently and are a lot stronger and weaker in different areas, making them very powerful tools for many machine learning projects.