based on the abovethe following diagram represents machine learning modeltask (tperforman ce (pexperienc (elet us discuss them more in detail nowtask(tfrom the perspective of problemwe may define the task as the real-world problem to be solved the problem can be anything like finding best house price in specific location or to find best marketing strategy etc on the other handif we talk about machine learningthe definition of task is different because it is difficult to solve ml based tasks by conventional programming approach task is said to be ml based task when it is based on the process and the system must follow for operating on data points the examples of ml based tasks are classificationregressionstructured annotationclusteringtranscription etc experience (eas name suggestsit is the knowledge gained from data points provided to the algorithm or model once provided with the datasetthe model will run iteratively and will learn some inherent pattern the learning thus acquired is called experience(emaking an analogy with human learningwe can think of this situation as in which human being is learning or gaining some experience from various attributes like situationrelationships etc supervisedunsupervised and reinforcement learning are some ways to learn or gain experience the experience gained by out ml model or algorithm will be used to solve the task