Custom Named Entity Recognition with Open Source NER Annotator and spaCy - NLP Python Tutorial
1littlecoder via YouTube
The Fastest Way to Become a Backend Developer Online
Master Agentic AI, GANs, Fine-Tuning & LLM Apps
Overview
AI, Data Science & Cloud Certificates from Google, IBM & Meta — 40% Off
One plan covers every Professional Certificate on Coursera. 40% off Coursera Plus Annual.
Unlock All Certificates
Learn how to create custom Named Entity Recognition (NER) models using Python, spaCy, and an open-source NER Annotator tool. This 29-minute tutorial guides you through the process of annotating text with custom entities, tags, and labels using the NER Annotator by tecoholic. Then, use the annotated data to train an English Natural Language Processing (NLP) model with spaCy, enabling it to recognize custom entities in new text. Gain hands-on experience with practical NLP techniques and tools, including the NER Annotator and spaCy library, to enhance your text analysis capabilities.
Syllabus
Custom Named Entity Recognition (NER) Open Source NER Annotator + spaCy | NLP Python
Taught by
1littlecoder