I was wondering how Question and Answering (Q&A) systems could be addressed via machine learning? You describe different algorithms in your book, from which some are related to Natural Language processing. Which algorithms are useful to dive into when implementing Q&A systems?
Laura thank you for your question! Yes, see ch18 on Seq2Seq models and see the recent TF2 branch and an implementation using a similar notebook/approach to the TensorFlow Neural MT example (Spanish to English). This is an Encoder / Decoder model that is like a Q&A answer for the Q is a translation. See: https://www.tensorflow.org/tutorials/text/nmt_with_attention
Ch18 in my book covers Seq2Seq which was the predecessor to this. You build a chat bot using Seq2Seq. In the TF2 repo in my GitHub: http://github.com/chrismattmann/MLwithTensorFlow2ed/tree/master/TFv2/ you can find an updated version of the notebook for ch18 that uses TFv2 similar to the Neural MT example to implement the chat bot.
--Chris
Now I am super curious what sports would be like if we allowed drugs and tiny ads.
SKIP - a book about connecting industrious people with elderly land owners