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A document titled 'Deep Learning Foundations, Architectures & Engineering Practice' is shared, likely covering fundamental concepts, architectures, and practical engineering aspects of deep learning.
Recommend a book for systematically learning the basics of large language models: 《Foundations of Large Language Models》, written by Tong Xiao and Jingbo Zhu from Northeastern University NLP Lab and NiuTrans Research.
A 178-page survey study from the University of Huddersfield covering math and generative AI foundations, titled 'The Little Book of Generative AI Foundations'.
This book covers foundational concepts of large language models, including pre-training, generative models, prompting, and alignment. It serves as a reference for students and practitioners in NLP.