The Complete Guide to NLP: Foundations, Techniques, and Large Language Models

Introduction

In the rapidly evolving field of Natural Language Processing (NLP), staying ahead of technological advancements while mastering foundational principles is crucial for professionals aiming to drive innovation. "Mastering NLP from Foundations to LLMs" addresses several critical issues in NLP through innovative methodologies. The book first presents common workflows with LLMs such as prompting via APIs and building a Langchain pipeline. From there, the book takes on heavier challenges. One significant challenge is managing multiple models and optimizing their performance for specific tasks. The book introduces the concept of using multiple LLMs in parallel, with each model specialized for a particular function, such as a medical domain or backend development in Python. This approach reduces overall model size and increases efficiency by leveraging specialized models rather than a single, monolithic one.

Another issue is optimizing resource allocation. The book discusses strategies like prompt compression for cost reduction, which involves compacting input prompts to minimize token count without sacrificing performance. This technique addresses the high costs associated with large-scale model deployments, offering businesses a cost-effective way to implement NLP solutions.

Additionally, the book explores fault-tolerant multi-agent systems using frameworks like Microsoft’s AutoGen. By assigning specific roles to different LLMs, these systems can work together to accomplish complex tasks, such as professional-level code generation and error checking. This method enhances the reliability and robustness of AI-assisted solutions.

Through these problem-solving capabilities, "

Author Bio

Lior Gazit is a highly skilled Machine Learning professional with a proven track record of success in building and leading teams drive business growth. He is an expert in Natural Language Processing and has successfully developed innovative Machine Learning pipelines and products. He holds a Master degree and has published in peer-reviewed journals and conferences. As a Senior Director of the Machine Learning group in the Financial sector, and a Principal Machine Learning Advisor at an emerging startup, Lior is a respected leader in the industry, with a wealth of knowledge and experience to share. With much passion and inspiration, Lior is dedicated to using Machine Learning to drive positive change and growth in his organizations.

Meysam Ghaffari is a Senior Data Scientist with a strong background in Natural Language Processing and Deep Learning. Currently working at MSKCC, where he specialize in developing and improving Machine Learning and NLP models for healthcare problems. He has over 9 years of experience in Machine Learning and over 4 years of experience in NLP and Deep Learning. He received his Ph.D. in Computer Science from Florida State University, His MS in Computer Science - Artificial Intelligence from Isfahan University of Technology and his B.S. in Computer Science at Iran University of Science and Technology. He also worked as a post doctoral research associate at University of Wisconsin-Madison before joining MSKCC.

The Complete Guide to NLP: Foundations, Techniques, and Large Language Models

Introduction

Author Bio

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The Complete Guide to NLP: Foundations, Techniques, and Large Language Models

Introduction

Author Bio

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