Starting with the basics! Linear Regression is perfect for predicting continuous numerical values. Its simplicity and interpretability make it a go-to model for many tasks. Here's a code snippet in Python:

Decision Trees are great for both classification and regression tasks. They can handle complex relationships in data. Check out the Python code snippet:

A powerhouse ensemble model! Random Forest combines multiple Decision Trees to improve accuracy and reduce overfitting. Here's the Python code:

GBMs create strong predictive models by combining weak learners sequentially. It's a powerful technique widely used in competitions! Check out the Python code:

The holy grail of ML! Neural Networks excel in handling complex tasks like image recognition, natural language processing, and more. Here's a code snippet using TensorFlow: