Mastering spaCy
Beginner
103 Lessons
30h
Certificate of Completion
Takeaway Skills
An understanding of spaCy’s architecture and its various components for NLP tasks
Ability to customize and train your own statistical models for NLP tasks
Ability to work with advanced NLP features
An understanding of how to build and optimize NLP pipelines
Practical experience with using spaCy for real-world NLP applications
Course Overview
This course offers an extensive introduction to the widely-used Python library, spaCy, for natural language processing (NLP). It covers spaCy basics, such as tokenization and part-of-speech tagging, as well as advanced topics like custom model training and NLP pipeline creation. The course has three parts: Part 1 focuses on spaCy's fundamentals, its architecture, installation, and setup. It teaches common NLP tasks like tokenization, named entity recognition (NER), part-of-speech (POS) tagging, and depen...Show More
Course Content
Getting Started
Core Operations with spaCy
Linguistic Features
Rule-Based Matchmaking
Working with Word Vectors and Semantic Similarity
Putting Everything Together: Semantic Parsing with spaCy
10 Lessons
Assessment: spaCy Features
Assessment
Customizing spaCy Models
8 Lessons
Text Classification with spaCy
10 Lessons
spaCy and Transformers
11 Lessons
Putting Everything Together: Designing a Chatbot with spaCy
10 Lessons
Appendix
4 Lessons
Conclusion
1 Lesson
Assessment - Machine Learning with spaCy
Assessment
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