Deep Learning - Artificial Neural Networks with Tensorflow - Why Keras?

The video explains why the Keras API is predominantly used in a TensorFlow 2 course, emphasizing that this choice aligns with Google's recommendations. It clarifies that using Keras simplifies the learning process by allowing students to leverage existing knowledge. The video also outlines when not to use Keras, such as when its capabilities are insufficient for specific tasks. Additionally, it provides a historical overview of Keras, highlighting its origins as a Theano wrapper and its evolution into a flexible API compatible with various backends.

Why is using the Keras API in a TensorFlow 2 course considered beneficial?

• It is not recommended by Google.

• It allows students to use new technology without learning many new things.

• It is only useful for advanced TensorFlow features.

• It makes the learning process more complex.

According to the course, when should you avoid using the Keras API?

• When the Keras API cannot perform the required task.

• When building a basic ANN or CNN.

• When Google advises against it.

• When using TensorFlow 1.

What was the original purpose of the Keras API?

• To be used exclusively with PyTorch.

• To serve as a standalone deep learning library.

• To act as a wrapper for Theano.

• To replace TensorFlow.

Who is the creator of the Keras API?

• Mark Zuckerberg

• Elon Musk

• Francois Chalet

• Sundar Pichai

What is a key feature of the Keras API that allows it to support multiple backends?

• It requires a specific backend to function.

• It is only compatible with Theano.

• It is an API that does not depend on specific implementations.

• It is a standalone library.