DIT884 - Advanced Topics In Data Science And Technologies, Python - Computer Science Assignment Help

Assignment Task

• Advanced Topics in Data Science and Technologies
• There exist many Deep learning Frameworks such as Theano, TensorFlow, Keras, PyTorch, and so  on. They can be classified as a low-level or high-level Deep Learning framework depending on the  level of abstraction they provide. 
• TensorFlow is a low-level Deep Learning Framework and is undoubtedly one of the most popular  and widely used DL frameworks in the Machine Learning community. TensorFlow 2 comes up with  a tight integration of Keras which is a high-level API for building deep neural networks and other ML  models. 
• Keras is the most popular high-level Deep Learning framework that provides a second-level  abstraction to Deep Learning model development. Other frameworks are also available, but Keras  has been the most widely adopted one. Keras is the official high-level API of TensorFlow for quick  and easy model design and training. 
• Keras is a high-level neural network API written in Python and can help you in developing a fully  functional DL model with less than twenty lines of code. Since it is written in Python, it has a larger  community of users and supporters and is extremely easy to get started with. In a nutshell, the code  you write in Keras gets converted to TensorFlow, which then runs on a compute instance.

Questions: 

1. Explain the role of each parameter (optimizer, metrics, losses, and activation functions) 2. For each parameter (optimizer, metrics, …), explain briefly the main available settings. 

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