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Applied Natural Language Processing with Python
Language: en
Pages: 150
Authors: Taweh Beysolow II
Categories: Computers
Type: BOOK - Published: 2018-09-11 - Publisher: Apress

Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will learn the skills to implement these methods in larger infrastructures to replace existing code or create new algorithms. Applied Natural
Applied Natural Language Processing in the Enterprise
Language: en
Pages: 336
Authors: Ankur A. Patel, Ajay Uppili Arasanipalai
Categories: Computers
Type: BOOK - Published: 2021-05-12 - Publisher: "O'Reilly Media, Inc."

NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and
Applied Natural Language Processing in the Enterprise
Language: en
Pages: 350
Authors: Ankur A Patel, Ajay Uppili Arasanipalai
Categories: Computers
Type: BOOK - Published: 2021-04-13 - Publisher:

NLP is one of the hottest topics in AI today. Having lagged for years behind other deep learning fields such as computer vision, NLP only recently gained mainstream popularity. Google, Facebook, and OpenAI have open-sourced large pretrained language models, but many organizations today still struggle with building and adopting NLP
Applied Natural Language Processing with Python
Language: en
Pages:
Authors: Taweh Beysolow
Categories: Machine learning
Type: BOOK - Published: 2018 - Publisher:

Books about Applied Natural Language Processing with Python
Applied Natural Language Processing in the Enterprise
Language: en
Pages: 336
Authors: Ankur A. Patel, Ajay Uppili Arasanipalai
Categories: Computers
Type: BOOK - Published: 2021-05-12 - Publisher: "O'Reilly Media, Inc."

NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and