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nexusstc/Blueprints for Text Analytics Using Python: Machine Learning Based Solutions for Common Real World (Nlp) Applications/c63f0fe6d74b904d41494495addce0ab.epub
Blueprints for Text Analytics Using Python: Machine Learning Based Solutions for Common Real World (Nlp) Applications 🔍
Jens Albrecht; Sidharth Ramachandran; Christian Winkler O'Reilly Media, Incorporated, 1st edition, Sebastopol, California, 2021
英语 [en] · EPUB · 8.6MB · 2021 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc · Save
描述
Turning text into valuable information is essential for many businesses looking to gain a competitive advantage. There have been many improvements in natural language processing and users have a lot of options when choosing to work on a problem. However, it's not always clear which NLP tools or libraries would work for a business use--or which techniques you should use and in what order. This practical book provides theoretical background and real-world case studies with detailed code examples to help developers and data scientists obtain insight from text online. Authors Jens Albrecht, Sidharth Ramachandran, and Christian Winkler use blueprints for text-related problems that apply state-of-the-art machine learning methods in Python. If you have a fundamental understanding of statistics and machine learning along with basic programming experience in Python, you're ready to get started. You'll learn how to: Crawl and clean then explore and visualize textual data in different formats Preprocess and vectorize text for machine learning Apply methods for classification, topic analysis, summarization, and knowledge extraction Use semantic word embeddings and deep learning approaches for complex problems Work with Python NLP libraries like spaCy, NLTK, and Gensim in combination with scikit-learn, Pandas, and PyTorch
备用文件名
lgli/Blueprints for Text Analytics Using Python - Machine Learning-Based Solutions for Common Real World (NLP) Applications.epub
备用文件名
lgrsnf/Blueprints for Text Analytics Using Python - Machine Learning-Based Solutions for Common Real World (NLP) Applications.epub
备选标题
Blueprints for text analysis using Python machine learning-based solutions for common real world (NLP) applications$dJens Albrecht, Sidharth Ramachandran and Christian Winkler
备选作者
Albrecht, Jens, Ramachandran, Sidharth, Winkler, Christian
备用版本
United States, United States of America
备用版本
First edition, revision, Bejing, 2020
备用版本
O'Reilly Media, Sebastopol, CA, 2020
备用版本
1, US, 2021
备用版本
1, 2020
元数据中的注释
lg3080698
元数据中的注释
{"edition":"1","isbns":["149207408X","9781492074083"],"last_page":350,"publisher":"O′Reilly"}
备用描述
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
开源日期
2021-08-02
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