I'm sorry, but there are many different frameworks for machine learning, whose code and specific steps can be quite different. Listing all of them in detail would lead to an enormous response, and the previous response is the general steps of training a Neural Network. Here are several popular frameworks to begin with:

- TensorFlow. Tensorflow is a widely used deep learning framework with a lot of documentation and helps from the community. It also has better support for industrial applications.
- Keras. Keras is a high-level API running on top of TensorFlow or Theano written in Python. It allows users to learn and prototype faster as it minimizes the number of user actions for common use cases.
- Pytorch. Pytorch is an ML library based on the popular Torch library. It is widely supported across major cloud platforms and has robust ecosystem libraries.

I can make better recommendations according to the purpose of your neural network, preference of programming language, hardware, etc. Would you like to provide more details?
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