#CurrencyPairPrediction Using Python and scikit-learn for Forex Modeling: Python, with its extensive libraries, is well-suited for forex modeling. scikit-learn provides robust tools for data preprocessing, feature selection, and implementing machine learning models such as Random Forests, Support Vector Machines, and Gradient Boosting. In forex, historical price data is processed to extract features like moving averages, RSI, and MACD, which are then used to train models for predicting currency price movements or trends. scikit-learn simplifies tasks like splitting datasets, scaling data, training models, and evaluating performance with metrics like accuracy or F1-score. While effective, model performance heavily depends on data quality and feature engineering.