Today I have learned about decision tree is a common tool in machine learning used for sorting data (classification) and predicting numbers (regression). It works by dividing the data into different areas, each with its own label or predicted number. Imagine the decision tree like an actual tree. Each point where the tree splits represents a decision made based on a certain piece of information. The branches show what happens after each decision, and the ends of the branches give the final answer or category.In learning about decision trees, a few main ideas stand out. The root node is at the very top of the tree and picks the best information to start splitting the data. The internal nodes are the splitting points where decisions are made based on different pieces of data. The branches are like pathways that show the results of these decisions. Lastly, the leaf nodes are where the tree ends, giving the final answer.