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Blueprints for text analysis using Python
Paperback
€63.99
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- Book Synopsis
- 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
- About The Author
- Jens Albrecht is a full-time professor for Computer Science Department at the Nuremberg Institute of Technology. His work focuses on data management and analytics with a focus on text. He holds a doctorates degree in computer science. Before he rejoined academia in 2012, he has been working for over a decade in the industry as consultant and data architect. He is author of several articles on Big Data management and analysis.
- Product Details
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- ISBN
- 9781492074083
- Format
- Paperback
- Publisher
- O'Reilly, (22 December 2020)
- Number of Pages
- 422
- Weight
- 742 grams
- Language
- English
- Dimensions
- 233 x 178 x 28 mm
- Categories: