Machine Learning Random Forest with Python from Scratch - Model and Training

The video tutorial introduces the concept of machine learning models, explaining that they are mathematical equations used to fit data and predict unseen data. It discusses the process of training models, choosing the right model and algorithm, and the importance of accuracy and error. The tutorial also covers linear models, hyperparameters, and provides examples of model training, such as spam email detection.

Discuss the importance of algorithms in training machine learning models.

What is the process of training a model using spam and normal emails?

What are overfitting and underfitting in the context of machine learning models?