Demystifying Building Natural Language Processing ML Models and How to Leverage Them By Example

Natural Language Processing (NLP) is rapidly reshaping industries, but building effective NLP models can seem complex and overwhelming for many developers. This session breaks down the process into manageable steps, beginning with a straightforward introduction to building NLP models from scratch. Attendees will be guided through the key stages of NLP model creation, including dataset preparation, model training, and evaluation, using accessible tools and libraries. We'll start by building a simple model to help attendees grasp foundational concepts, setting them up for success in more advanced projects.

From there, we'll construct a more involved redaction model, a critical tool for securing text-sensitive data. This practical example will help attendees understand how to solve more complex NLP problems and how to build models that handle specific tasks like identifying and redacting confidential information. The session will conclude with practical code samples and resources that participants can take away, giving them a clear roadmap for implementing these NLP techniques in their work. Whether you're just starting with NLP or looking to take your skills to the next level, this session provides a clear, actionable formula for success.