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How to ace Exploratory Data Analysis for Natural Language

Exploratory Data Analysis (EDA) is a crucial component in any machine learning process, which also holds for Natural Language (NLP) projects. However, one important question arises: what are the best methods to explore, analyze, and visualize text data? Let’s dive into this exploration.

Exploratory Data Analysis for Natural Language

EDA can help data scientists understand the main themes, frequently occurring words, and general style of content, which can be a foundational step in preparing for more advanced NLP tasks, where a deep understanding of the data’s characteristics is required.

EDA key benefits for NLP tasks

Performing EDA on text data is challenging due to its unstructured and complex nature, requiring methods different from those used for numerical data for analysis and visualization.