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Natural Language Processing: Foundations, Applications, and Future

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Manage episode 492461151 series 3485568
Content provided by Rick Spair. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Rick Spair or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

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A comprehensive overview of Natural Language Processing (NLP), beginning by defining it as a multidisciplinary field focused on enabling computers to understand, interpret, and generate human language. It details the historical progression of NLP through symbolic, statistical, and neural eras, culminating in the rise of Large Language Models (LLMs). The text then breaks down the mechanics of language understanding via the NLP pipeline, explaining processes like tokenization, syntactic analysis, and semantic analysis. Finally, it explores diverse applications of NLP across industries such as healthcare, finance, and legal tech, while also addressing significant challenges including ambiguity, computational cost, and ethical concerns like bias and privacy, before looking to the future of multimodal and explainable AI.

  continue reading

117 episodes

Artwork
iconShare
 
Manage episode 492461151 series 3485568
Content provided by Rick Spair. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Rick Spair or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

Send us a text

A comprehensive overview of Natural Language Processing (NLP), beginning by defining it as a multidisciplinary field focused on enabling computers to understand, interpret, and generate human language. It details the historical progression of NLP through symbolic, statistical, and neural eras, culminating in the rise of Large Language Models (LLMs). The text then breaks down the mechanics of language understanding via the NLP pipeline, explaining processes like tokenization, syntactic analysis, and semantic analysis. Finally, it explores diverse applications of NLP across industries such as healthcare, finance, and legal tech, while also addressing significant challenges including ambiguity, computational cost, and ethical concerns like bias and privacy, before looking to the future of multimodal and explainable AI.

  continue reading

117 episodes

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