1145 text preprocessing in python

Fernando-Iscar commented 6 months ago

Hi @shrabasteebanerjee,

Based on our work together, I've completed this topic on Text preprocessing in Python. With this one, now we have text preprocessing content in R and Python, leading to a seamless introduction to future topics on NLP algorithms like TF-IDF and BERT within the Machine Learning section.

The outline is the following:

Overview: Introduction to the significance of text preprocessing in the big data era, highlighting its impact on analytics and decision-making.
Introduction to Text Preprocessing: Discussion of challenges in converting text into a numerical format for machine learning models and an introduction to NLP's role.
Natural Language Processing (NLP): Explanation of NLP and its importance in AI, along with a rundown of key preprocessing techniques.
Tokenization: A dive into the tokenization process with code examples using spaCy.
Stemming vs. Lemmatization: Comparison of these two techniques with examples, explaining their importance in text normalization.
Practical Example: Hands-on example detailing the steps for loading, cleaning, and preprocessing text data from subreddit descriptions. I have used some code snippets from our project.
Visualizing Data Before and After Preprocessing: Visual evidence of the text transformation through word clouds and bar plots, highlighting the shift from generic to specific terms.
Conclusion: Summary of the tutorial's key points and the impact of preprocessing on preparing data for sophisticated NLP tasks.

Looking forward to your feedback!

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shrabasteebanerjee commented 5 months ago

looks great @Fernando-Iscar , i am merging :)

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