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Advanced NLP with spaCy is an open-source educational repository that provides the materials for an interactive course on advanced natural language processing using the spaCy library. The course is designed to teach developers how to build real-world NLP systems by combining rule-based techniques with machine learning models. The repository includes lessons, exercises, and examples that guide learners through tasks such as tokenization, named entity recognition, text classification, and training custom NLP models. It also demonstrates how spaCy pipelines work and how developers can extend them with custom components and training data. The course is structured as a hands-on learning environment where students can run code examples, experiment with NLP techniques, and build practical language processing applications. Because spaCy is widely used in production environments, the course emphasizes industrial-strength NLP workflows and best practices.
Features
- Interactive course teaching natural language processing with spaCy
- Hands-on exercises covering tokenization, entity recognition, and text classification
- Examples demonstrating rule-based and machine learning NLP approaches
- Training workflows for creating custom NLP models
- Educational notebooks and scripts for experimenting with language processing
- Practical guidance for building real-world NLP applications
Project Samples
