#CurrencyPairPrediction Feature Extraction (Vectorization) Convert text into numbers so ML models can understand it: • Bag of Words (BoW): Simple word counts • TF-IDF (Term Frequency-Inverse Document Frequency): Weigh rare but important words higher • Word Embeddings: • Word2Vec, GloVe (pre-trained vector spaces) • Finance-specific embeddings (e.g., FinBERT) Embeddings capture semantic meaning: (e.g., “profit” and “earnings” are close in the vector space).