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
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

Blueprints for Text Analytics Using Python: Machine Learning-Based Solutions for Common Real World (NLP) Applications
422
Blueprints for Text Analytics Using Python: Machine Learning-Based Solutions for Common Real World (NLP) Applications
422Product Details
ISBN-13: | 9781492074083 |
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Publisher: | O'Reilly Media, Incorporated |
Publication date: | 01/12/2021 |
Pages: | 422 |
Product dimensions: | 7.00(w) x 9.19(h) x (d) |