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Graph Theory Book questions

 
Ranch Hand
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As always, I will be excited to learn about the Graph Theory for AI. But since there is a lot of hype then reality in most of the publications and books so I have few questions if someone can answer.


1-I personally thing Graph Theory is mostly related to Deep learning. The question is do we really need to learn Graph theory to understand neural networks ?

2-A part from deep learning, is there any other area in Artificial Intelligence where we can leverage Graph Theory. If yes where ?

3-Does this book has some hands on exercises ?


Thanks
Awais Bajwa
 
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Hi Awais,

Our focus in this book is on using graph algorithms for analysis and feature engineering for machine learning. (More classical graph theory uses.) We do not include any content on neural networks.  However, our team is extremely interested in Graph Native Learning as outlined in the Google DeepMind paper: https://blog.acolyer.org/2018/09/19/relational-inductive-biases-deep-learning-and-graph-networks/.  We believe that in the future people will be running ML/DL inside graphs but this is going to take time to emerge.

1 - I don't believe you must learn graph theory to understand NN but as I mentioned above, I believe they point to some promising directions. And Graph Theory itself is just plain fun.
2- Graphs help with AI in 2 big ways today:
  • For graph feature engineering because relationships are often the strongest predictors of behavior. This is the focus on chapter 8 of the book.
  • By using Knowledge Graphs to help AI systems make better heuristic decisions by adding context.

  • 3 - Yes!  There are many many examples with sample data and code on github you can play with.

     
    Awais Bajwa
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    Thanks Amy for the reply.


    Does your book ask helps readers understanding the graph databases as well?
     
    Amy Hodler
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    We did not include information about graph databases because it was well covered in another O'Reilly book. If you're interested in the Neo4j Graph Database, there is a book with that focus: https://neo4j.com/lp/book-graph-databases


     
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    A neural network is a graph. The very name "network" indicates that.

    As to whether you need to know graph theory to understand neural nets? I don't think it's actually necessary, but it can't hurt. Everyone should know a little graph theory. You never know when it might come in handy.
     
    Amy Hodler
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    Very True Tim!

    I'm often thinking about graphs from the analsys perspective (i.e. Graph Theory stuff) which of course is just one area.  

    (graphs)-[ARE]->(everywhere)  

    :-)  

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