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Language Pattern Analysis in Python

In this session we use text analysis to look at language patterns in a review dataset.
Richie Cotton
Maham Khan
Richie Cotton, Maham Khan

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실습 문제하고 트랙하세요.

Google로 계속하기계속 진행하시면 다음 사항에 동의하는 것으로 간주됩니다: 이용약관 및 개인정보 처리방침 그리고 귀하의 데이터가 미국에 저장된다는 점에 동의하는 것으로 간주됩니다.

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From online reviews to social media posts, unstructured text data holds valuable insights—if you know how to extract them. In this session, you’ll learn how to turn raw text into meaningful metrics using Python, applying natural language processing (NLP) techniques to real-world data. You’ll walk through every step, from scraping the data to visualizing the results.In this code-along webinar, Maham Khan will guide you through analyzing professor ratings using the nltk package. You’ll learn how to collect and clean text data, extract quantitative features, and create visualizations that reveal patterns and sentiment. By the end, you’ll have a practical workflow you can apply to any text dataset.

Key takeaways

  • Learn how to apply a web scraper to create a corpus of freelancer reviews

  • Learn how to label the reviews based upon pre-defined conditions

  • Identify language (words and phrases) used more often for freelancers based on different personas, and study how this language varies by field

주제

Data ScienceData AnalysisPython

관련

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