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Natural Language Processing Tools

2 posts · Dec 2022 – Apr 2023

What this trail covers

Hex has introduced capabilities for Natural Language Processing (NLP) in Python, enabling users to programmatically understand and interpret human language. This includes basic text processing using libraries like NLTK for tasks such as tokenization and frequency distribution, sentiment analysis using VADER, and an introduction to topic modeling with Gensim. The platform facilitates the application of these NLP techniques within the Hex environment for data analysis and insight generation.

All Hex trails
  1. Natural Language Processing in PythonThis post introduces Natural Language Processing (NLP) capabilities within the Hex platform. It details how to use Python libraries such as NLTK for tokenization, word frequency analysis, and stop word removal. It also covers sentiment analysis using NLTK's VADER lexicon and provides an introductory overview of topic modeling with the Gensim library. The post demonstrates practical applications of these NLP techniques, including analyzing text from web pages and social media, and highlights the importance of text cleaning and preparation.
  2. Text cleaning for NLP with PythonThis post details text cleaning techniques for NLP tasks in Python, including normalization (lowercasing), removal of unwanted characters (emojis, mentions, URLs, punctuation), stop word removal using NLTK, and both lemmatization and stemming. It provides code examples for each step and combines them into a pipeline function for processing text data, demonstrating its application on a sample dataset.