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

  • An understanding of NLP concepts
  • Python programming experience

Audience

  • Data scientists
  • Developers
  14 Hours
 

Number of participants


Starts

Ends


Dates are subject to availability and take place between 9:30 am and 4:30 pm.
Open Training Courses require 5+ participants.

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