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Blueprints for Text Analytics Using Python - Jens Albrecht

Blueprints for Text Analytics Using Python

By: Jens Albrecht, Sidharth Ramachandran, Christian Winkler

eText | 4 December 2020 | Edition Number 1

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Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always clear which NLP tools or libraries would work for a business's needs, or which techniques you should use and in what order.

This practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler provide real-world case studies and detailed code examples in Python to help you get started quickly.

  • Extract data from APIs and web pages
  • Prepare textual data for statistical analysis and machine learning
  • Use machine learning for classification, topic modeling, and summarization
  • Explain AI models and classification results
  • Explore and visualize semantic similarities with word embeddings
  • Identify customer sentiment in product reviews
  • Create a knowledge graph based on named entities and their relations
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Non-FictionComputing & I.T.DatabasesData MiningGraphical & Digital Media Applications3D Graphics & ModellingComputer ScienceArtificial IntelligenceNatural Language & Machine TranslationMachine LearningComputer Programming & Software DevelopmentProgramming & Scripting Languages

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