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Mastering NLP from Foundations to LLMs

Mastering NLP from Foundations to LLMs

By : Gazit, Meysam Ghaffari
4.9 (24)
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Mastering NLP from Foundations to LLMs

Mastering NLP from Foundations to LLMs

4.9 (24)
By: Gazit, Meysam Ghaffari

Overview of this book

Do you want to master Natural Language Processing (NLP) but don’t know where to begin? This book will give you the right head start. Written by leaders in machine learning and NLP, Mastering NLP from Foundations to LLMs provides an in-depth introduction to techniques. Starting with the mathematical foundations of machine learning (ML), you’ll gradually progress to advanced NLP applications such as large language models (LLMs) and AI applications. You’ll get to grips with linear algebra, optimization, probability, and statistics, which are essential for understanding and implementing machine learning and NLP algorithms. You’ll also explore general machine learning techniques and find out how they relate to NLP. Next, you’ll learn how to preprocess text data, explore methods for cleaning and preparing text for analysis, and understand how to do text classification. You’ll get all of this and more along with complete Python code samples. By the end of the book, the advanced topics of LLMs’ theory, design, and applications will be discussed along with the future trends in NLP, which will feature expert opinions. You’ll also get to strengthen your practical skills by working on sample real-world NLP business problems and solutions.
Table of Contents (14 chapters)
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Prompt compression and API cost reduction

This part is dedicated to a recent development in resource optimization for when employing API-based LLMs, such as OpenAI’s services. When considering the many trade-offs between employing a remote LLM as a service and hosting an LLM locally, one key metric is cost. In particular, based on the application and usage, the API costs can accumulate to a significant amount. API costs are mainly driven by the number of tokens that are being sent to and from the LLM service.

In order to illustrate the significance of this payment model on a business plan, consider business units for which the product or service relies on API calls to OpenAI’s GPT, where OpenAI serves as a third-party vendor. As a particular example, imagine a social network that lets its users have LLM assistance to comment on posts. In that use case, a user is interested in commenting on a post, and instead of having to write a complete comment, a feature lets the...

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