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Mastering spaCy
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Getting Started
Introduction to the Course
Overview: Getting Started
NLP and Python
Python String Operations
High-level Overview of the spaCy Library
Visualization with displaCy
Summary: Getting Started
Quiz: Getting Started
Exercise: Getting Started
Solution: Getting Started
Core Operations with spaCy
Overview: Core Operations with spaCy
Overview of spaCy Conventions
Introducing Tokenization
Customizing the Tokenizer and Sentence Segmentation
Understanding Lemmatization
spaCy Container Objects
More spaCy Features
Summary: Core Operations with spaCy
Quiz: Core Operations with spaCy
Exercise: Core Operations with spaCy
Solution: Core Operations with spaCy
Linguistic Features
Overview: Linguistic Features
POS Tagging
POS Tagging - Continued
Introduction to Dependency Parsing
Introducing NER
Merging and Splitting Tokens
Summary: Linguistic Features
Quiz: Linguistic Features
Exercise: Linguistic Features
Solution: Linguistic Features
Rule-Based Matchmaking
Overview: Rule-Based Matchmaking
Token Based Matching
Syntax Support and Regex
PhraseMatcher and EntityRuler
Combining spaCy Models and Matchers
Summary: Rule-Based Matchmaking
Quiz: Rule-Based Matchmaking
Exercise: Rule-Based Matchmaking
Solution: Rule-Based Matchmaking
Working with Word Vectors and Semantic Similarity
Overview: Word Vectors and Semantic Similarity
Understanding Word Vectors
Using spaCy's Pre-trained Vectors
The Similarity Method
Advanced Semantic Similarity Methods
Summary: Word Vectors and Semantic Similarity
Quiz: Working with Word Vectors and Semantic Similarity
Exercise: Word Vectors and Semantic Similarity
Solution: Word Vectors and Semantic Similarity
Putting Everything Together: Semantic Parsing with spaCy
Overview: Semantic Parsing with spaCy
Extracting Named Entities
Using Dependency Trees For Extracting Entities
Using Dependency Relations for Intent Recognition
Semantic Similarity Methods for Semantic Parsing
Putting It All Together
Summary: Semantic Parsing with spaCy
Quiz: Semantic Parsing with spaCy
Exercise: Semantic Parsing with spaCy
Solution: Semantic Parsing with spaCy
Course Assessment
Assessment: spaCy Features
Customizing spaCy Models
Overview: Customizing spaCy Models
Getting Started with Data Preparation
Updating an Existing Pipeline Component
Training a Pipeline Component From Scratch
Summary
Quiz: Customizing spaCy Models
Exercise: Customizing spaCy Models
Solution: Customizing spaCy Models
Text Classification with spaCy
Overview: Text Classification with spaCy
Understanding the Basics of Text Classification
Training the spaCy Text Classifier
Sentiment Analysis with spaCy
Text classification with spaCy and Keras
Embedding Words
Summary: Text Classification with SpaCy
Quiz: Text Classification with spaCy
Exercise: Text Classification with spaCy
Solution: Text Classification with spaCy
spaCy and Transformers
Overview: spaCy and Transformers
Transformers and Transfer Learning
Understanding BERT
Transformers and TensorFlow
Using BERT for Text Classification
Using Transformer Pipelines
Transformers and spaCy
Summary: spaCy and Transformers
Quiz: spaCy and Transformers
Exercise: spaCy and Transformers
Solution: spaCy and Transformers
Putting Everything Together: Designing a Chatbot with spaCy
Overview: Designing a Chatbot with spaCy
Introduction to Conversational AI
Getting to Know the Dataset
Entity Extraction
Intent Recognition
Classifying Text with a Character-level LSTM
Differentiating Subjects from Objects
Anaphora Resolution
Summary: Designing a Chatbot with spaCy
Quiz: Designing a Chatbot With spaCy
Appendix
Installing spaCy
Installing spaCy's Statistical Models
More on Visualization with displaCy
Saving and loading custom models
Conclusion
Conclusion
Course Assessment
Assessment - Machine Learning with spaCy
Summary: Rule-Based Matchmaking
Let's go over what we have learned.
Key Points
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