e-hossam96/CMU-CS11-711
Solutions of the CMU Advanced Natural Language Processing Course
This repository provides working solutions and code implementations for core assignments from an advanced Natural Language Processing (NLP) course. It details how foundational NLP concepts, like neural networks and the Transformer architecture, are built from scratch. Students and researchers interested in understanding the inner workings of modern NLP models would find this useful.
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Use this if you are an NLP student, researcher, or practitioner who wants to see concrete implementations of advanced NLP algorithms and architectures, such as self-attention and computational graphs.
Not ideal if you are looking for a pre-built tool or library to apply NLP to a specific business problem without needing to understand the underlying code.
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Dec 08, 2022
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