Linux for Beginners May Linux Tricks and Tips March 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 Blueprints for Text Analytics Using Python practical book provides data scientists and developers with blueprints for best practice solutions to common tasks in text analytics and natural language processing.
Leave a Reply Cancel reply Your email address will not be published. Notify me of follow-up comments by email. Notify me of new posts by email. This site uses Akismet to reduce spam. Learn how your comment data is processed. Programmer Books. Random Books. Book Description: Derive useful insights from your data using Python. This book: Provides complete coverage of the major concepts and techniques of natural language processing NLP and text analytics Includes practical real-world examples of techniques for implementation, such as building a text classification system to categorize news articles, analyzing app or game reviews using topic modeling and text summarization, and clustering popular movie synopses and analyzing the sentiment of movie reviews Shows implementations based on Python and several popular open source libraries in NLP and text analytics, such as the natural language toolkit nltk , gensim, scikit-learn, spaCy and Pattern.
This Blueprints for Text Analytics Using Python 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.
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