Overview
TextBlob is a Python NLP library for processing textual data. It provides a simple API that makes it easy to perform NLP tasks, such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, etc.
This instructor-led, live training (online or onsite) is aimed at data scientists and developers who wish to use TextBlob to implement and simplify NLP tasks, such as sentiment analysis, spelling corrections, text classification modeling, etc.
By the end of this training, participants will be able to:
- Set up the necessary development environment to start implementing NLP tasks with TextBlob.
- Understand the features, architecture, and advantages of TextBlob.
- Learn how to build text classification systems using TextBlob.
- Perform common NLP tasks (Tokenization, WordNet, Sentiment analysis, Spelling correction, etc.)
- Execute advanced implementations with simple APIs and a few lines of codes.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Requirements
- An understanding of NLP concepts
- Python programming experience
Audience
- Data scientists
- Developers
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