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Course Outline
Introduction
- Overview of TextBlob features and architecture
- NLP fundamentals
Getting Started
- Installing TextBlob
- Importing libraries and data
Building Text Classification Models
- Loading data and creating classifiers
- Evaluating classifiers
- Updating classifiers with new data
- Using feature extractors
Performing NLP Tasks using TextBlob
- Tokenization
- WordNet integration
- Noun phrase extraction
- Part-of-speech tagging
- Sentiment analysis
- Spelling correction
- Translation and language detection
APIs and Advanced Implementations
- Sentiment analyzers
- Tokenizers
- Noun phrase chunkers
- POS taggers
- Parsers
- Blobber
Troubleshooting
Summary and Next Steps
Requirements
- Familiarity with core NLP concepts.
- Practical experience with Python programming.
Target Audience
- Data scientists.
- Software developers.
14 Hours
