We will go about this intelligently. There are a lot of pipeline model structures made by Google using different networks in their TensorFlow library. What we'll do here is take one of those model structures and networks and modify the code to our needs.
This is good because we won't waste our time building a pipeline from scratch and won't have to worry about incorporating the TensorBoard visualization stuff as it is already present in the Google pipeline models.
We will use a pipeline model from here:
https://github.com/tensorflow/models/
As you can see, there are a lot of different models made in TensorFlow in this repository. You can dive deeper into some models that are related to natural language processing (NLP), recursive neural networks, and other topics. This is a really good place to start if you want to understand complex models.
For this...
