In this chapter, we have been introduced to machine learning in the context of finance. We discussed how AI and machine learning is transforming the financial sector. Machine learning can be supervised or unsupervised, and supervised algorithms can be regression-based and classification-based. The scikit-learn Python library provides various machine learning algorithms and risk metrics.
We discussed the use of regression-based machine learning models such as OLS regression, ridge regression, LASSO regression, and elastic net regularization in predicting continuous values such as security prices. An ensemble of decision trees was also discussed, such as the bagging regressor, gradient tree boosting, and random forests. To measure the performance of regression models, we visited the MSE, MAE, explained variance score, and R2 score.
Classification-based machine learning classifies...
