一緒にコーディング:
コードアロング ↗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
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Python Sentiment Analysis Tutorial
We help simplify sentiment analysis using Python in this tutorial. You will learn how to build your own sentiment analysis classifier using Python and understand the basics of NLP (natural language processing).
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Latent Semantic Analysis using Python
In this tutorial, you will learn how to discover the hidden topics from given documents using Latent Semantic Analysis in python.
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NLTK Sentiment Analysis Tutorial for Beginners
Python NLTK (natural language toolkit) sentiment analysis tutorial. Learn how to create and develop sentiment analysis using Python. Follow specific steps to mine and analyze text for natural language processing.



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