WEEK 08

PROGRESS: 1 / 8

NLP // TEXT ANALYSIS [ACTIVE SESSION]

SUMMARY // WHAT WE LEARNED

📝 Text Preprocessing: Cleaning text by lowercasing, removing punctuation, and filtering out stop words.
✂️ Stemming & Lemmatization: Reducing words to their root forms to normalize the text data.
🔢 Text to Vector: Converting human language into numerical representations that machine learning models can process.
🛍️ Bag of Words (BoW): Representing documents as a tally of word counts, ignoring grammar and word order.
📊 TF-IDF: Weighing word importance based on its frequency in a document relative to its frequency across the entire corpus.

CORE MATERIALS

BONUS MATERIALS