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Optimize LLMs for Specific Business Needs

by Daryle Serrant

Bridge the gap between the advanced capabilities of large language models and real-world business solutions. This course will teach you how to adapt large language models to achieve specific business objectives in an efficient and effective manner.

What you'll learn

Since the release of ChatGPT, Dolly, PaLM, and other large language models (LLMs), an increasing number of companies are seeking to leverage these technologies to address business-specific or industry-specific problems. A challenge many organizations face is optimizing LLMs to adequately meet unique demands while also ensuring ethical compliance.

In this course, Optimize LLMs for Specific Business Needs, you will gain the ability to tailor LLMs to accomplish specific business challenges and objectives.

First, you’ll explore the role of LLMs in addressing business opportunities and learn how they can be tailored to meet industry requirements.

Next, you’ll discover the intricacies involved in adapting, fine-tuning, and optimizing models for specific use cases, including methods for integrating domain-specific knowledge into LLMs and several techniques for optimizing computation and memory utilization of these models in production environments.

Finally, you’ll learn testing and validation strategies for LLMs in business applications and how to continuously refine LLMs based on real world-usage.

When you’re finished with this course, you’ll have the skills and knowledge of LLMs needed to effectively integrate these tools into your organization.

Table of contents

About the author

Daryle has worked as a data scientist and software engineer for industry giants such as Tesla and Lockheed Martin, as well as companies in the Aerospace and Defense, Consumer Electronics, Health and Wellness, and Renewable Energy sectors. He excels in leveraging machine learning to automate and streamline operations, and has crafted software products spanning the technology spectrum, from web and mobile applications to embedded systems. Amid his ventures in the tech world, Daryle discovered a pr... more

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