Mastering spaCy
By External Provider
About this course
This course teaches advanced techniques in Natural Language Processing (NLP) using spaCy and spaCy-LLM. You’ll learn how to integrate LLMs into your NLP workflows, creating custom components and models. Designed for both beginners and experienced developers, this course provides hands-on examples to help you master spaCy’s core functionalities. It equips you to apply transformer models and fine-tune them for specialized NLP tasks. What sets this course apart is its practical approach. You’ll learn to build end-to-end NLP workflows and gain skills in deploying production-ready solutions, making it ideal for real-world applications. This course is perfect for NLP engineers, machine learning developers, and software engineers. A basic understanding of Python and NLP concepts is recommended for the best experience.
What you will learn
- Build custom NLP components and integrate them into spaCy workflows
- Fine-tune transformer models for specialized NLP tasks
- Develop end-to-end NLP workflows using spaCy-LLM and FastAPI
- Apply advanced NLP techniques for semantic extraction and coreference resolution