Linear regression is one of the simplest and most widely used algorithms for predictive modeling.
Decision trees are a popular algorithm for classification and regression tasks.
Random forest is an ensemble learning method that combines multiple decision trees to improve predictive accuracy and control overfitting.
Gradient boosting machines ensemble learning technique that builds models sequentially, with each new model correcting errors made by the previous ones.
LSTM networks are a type of recurrent neural network (RNN) designed to handle sequential data and capture long-term dependencies.