Mathematical Rationale Behind the Machine Learning Algorithms Employed

• Random Forest: Explain the ensemble learning concept where multiple decision trees are combined to improve the model's robustness and accuracy. The mathematical rationale involves averaging the predictions from individual trees to reduce variance and improve generalization.

• LSTM (Long Short-Term Memory) Networks: Dive into the gating mechanisms of LSTM units, which are crucial for learning long-term dependencies. The update gate, forget gate, and output gate in LSTMs are defined by specific sigmoid and tanh functions, allowing the network to retain or forget information selectively.