From: ram@zedat.fu-berlin.de   
      
   Mike Spencer  wrote or quoted:   
   >Can someone suggest books at more or less the same level of   
   >technicality that that I might look at to catch up a bit on how neural   
   >nets are now constructed, trained, connected etc. to produce what is   
   >being called "large language models"?   
      
     From short to long:   
      
     "The Little Book of Deep Learning" - François Fleuret   
     (GPT in section 5.3 "Attention Models")   
      
     "Understanding Deep Learning" - Simon J.D. Prince (section 12.5   
     "Transformers for natural language processing")   
      
     "Dive into Deep Learning" - Aston Zhang, Zachary C. Lipton,   
     Mu Li, And Alexander J. Smola (chapter 11 "Attention   
     Mechanisms and Transformers")   
      
     Hands-on:   
      
     "The Complete Guide to Deep Learning with Python Keras, Tensorflow,   
     And Pytorch" - Joseph G. Derek (section 15.4 "NLP Applications:   
     Chatbots, Sentiment Analysis Tools") - only conditionally   
     recommended due to deficiencies in source code formatting   
      
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