Mastering Natural Language Processing Part 1: NLP Fundamental Principles and Applications

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Mastering Natural Language Processing Part 1: NLP Fundamental Principles and Applications

Published 8/2024
Duration: 17m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 56 MB
Genre: eLearning | Language: English

Mastering Natural Language Processing Part 1 explores the evolution, fundamentals, and responsible use of Natural Language Processing (NLP), encompassing practical applications and techniques in Python.
The course starts with an insightful exploration of NLP's history, tracing its evolution from rule-based approaches to the current era of deep learning and large language models. This segment unveils the transformative impact of cutting-edge technologies that have significantly shaped the NLP landscape, ushering in a new era of sophisticated language understanding. The course then delves into practical applications of NLP, focusing on Python implementations. Viewers will explore diverse use cases, including text summarization, machine translation, information extraction, and question-answering. As the course progresses, it concludes by unpacking the basics of NLP, covering essential topics such as string manipulation, token understanding, and intent recognition.
Upon completion, viewers will fully understand NLP concepts, techniques, and applications, empowering them to address real-world challenges in natural language processing.
What you will learn
Understand the historical development of Natural Language Processing, from rule-based approaches to the contemporary era of deep learning and large language models.Explore the transformative impact of cutting-edge technologies that have significantly shaped the NLP landscapeLearn practical applications of NLP with a focus on Python implementationsGain insights into the fundamental principles of NLP, covering essential topics such as string manipulation, token understanding, and intent recognition.
Who this video is for
Data scientists, AI practitioners, IT and technology professionals, academics and researchers, and consultants.

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