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https://t.co/mufRfyinDT
"Natural Language Processing and Large Language Models" is a new open-access Springer book by Chengqing Zong, Yang Zhao, and Yanjun Ma. It has almost 400 pages and provides an introduction to modern natural language processing and large language models.
The book covers neural networks, distributed representations, language models, Transformers, BERT, GPT, tokenization, sentiment classification, information extraction, text summarization, machine reading comprehension, machine translation, question answering, and RLHF.
I think it is a useful resource for anyone who wants an accessible introduction to these concepts. I suggest saving it as a reference.
https://t.co/T2GG3Y94Q7
An absolute banger of a paper.
"A Gentle Introduction to Matrix Calculus" by econometrics legend Jan Magnus — one of the clearest explanations of matrix derivatives ever written. Published in the Journal of Econometrics in 2024.
If you work in econometrics, machine learning, statistics or optimisation, this paper is pure gold.
Free, in my Awesome Math Books list (econometrics section)
https://t.co/soOYrEQ2he