From the course: Introduction to NLP and LLMs: Principles and Practical Applications

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Understanding large language models (LLMs)

Understanding large language models (LLMs)

- [Instructor] Let's look at large language models or LLMs. LLMs are capable of extracting insights from vast amounts of data, including structured data like sales figures and tables, which they might convert into a textual representation, such as, "In Q3, sales of Product A increased by 15% while sales of Product B decreased by 5%." LLMs also directly analyze the nuances of unstructured text data, like product manuals, legal contracts, internal memos, customer reviews, marketing reports and social media conversations. For example, marketing agencies use LLMs to analyze unstructured online data, like social media posts and reviews to understand brand perception and identify market trends, which can generate actionable insights for improved brand management and more effective marketing campaigns. LLMs are powerful because they are trained on massive data sets of diverse data, including text, code, images, audio and video from sources like books, academic journals, code repositories…

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