🗣️ Natural Language Processing
Text analysis, classification, and language understanding techniques
📰 Text Classification
Categorize text documents using traditional ML and deep learning
- TF-IDF + Traditional ML
- Pipeline Comparison
- CLIP Zero-shot
- BERT Fine-tuning
💬 Sentiment Analysis
Detect emotions and opinions in text data
- Rule-based approaches
- ML classifiers
- Pre-trained models
- Aspect-based sentiment
🏷️ Named Entity Recognition
Extract entities like names, locations, organizations from text
- Rule-based NER
- CRF models
- BiLSTM-CRF
- Transformer NER
❓ Question Answering
Build systems that answer questions based on context
- Extractive QA
- Reading comprehension
- BERT for QA
- Open-domain QA
📝 Text Generation
Generate coherent text using language models
- Language modeling
- RNN generation
- GPT-style models
- Controlled generation
🔤 Embeddings
Learn vector representations of words and sentences
- Word2Vec & GloVe
- FastText
- Sentence embeddings
- Contextual embeddings