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4- Social Buzz AI - Natural Language Processing (NLP) - Class 1

A repository for research, implementation, and best practices with Gradient Boosting methods (GBM, XGBoost, LightGBM), H2O AutoML, and robust strategies for modeling extreme class imbalance ("Low Default") in data science for finance and risk.

Course: Humanistic AI & Data Science (4th Semester)
Institution: PUC-SP
Professor: ✨ Rooney Ribeiro Albuquerque Coelho

Tip

This repository 2-social-buzz-ai-GBoost-and-LowDefault-Modeling is part of the main project 1-social-buzz-ai-main. To explore all related materials, analyses, and notebooks, visit the main repository

• 1-social-buzz-ai-main Part of the Humanistic AI Research & Data Modeling Series — where data meets human insight.

Important

⚠️ Heads Up

• Projects and deliverables may be made publicly available whenever possible.

• The course prioritizes hands-on practice with real data in consulting scenarios.

• All activities comply with the academic and ethical guidelines of PUC-SP.

• Confidential information from this repository remains private in private repositories.

Tip

• Access Workbook - (Class 1)

• Access: 🇬🇧 1- NLP_Pre_Processing_ENGLISH

• Access: 🇧🇷 1-Code NLP_Pre_Processing_Portuguese

• Access: NLP - Class 2 Repo

🎥 DEMO - NLP Cascade Pre-Processing Pipeline

1- NLP Pre Processing Regex

1-NLP_PreProcessing_Regex.mov

2- NLP Pre Processing Tokenizer using NLTK

  

2-NLP_PreProcessing_Tokenizer.using.NLTK.mov

3- NLP Preprocessing Pipeline – Lemmatization with SpaCy

3-NLP_PreProcessing_.Lemma.mov

4- NLP Pre Processing Stem

4-NLP_PreProcessing_Radicalisation.mov

5- NLP Pre Processing - Count Vectorizer (Bag-of-Words) - ConvertsTex into Feature - CountMatrix

5-NLP_PreProcessing_Count.Vectorizer.Bag-of-Words._.ConvertsTex_.into_Featur_.CountMatrix.mov

6- NLP Pre Processing - Stopword Removal – Remove Common Words (Stopwords)

6-NLP_PreProcessing_Stopword.Removal.Remove.Common.Words.Stopwords.1.mov

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