figure - defining the components of learning algorithm we can simplify the definition as follows machine learning is field that consists of learning algorithms thatimprove their performance at executing some task over time with experience while we discuss at length each of these entities in the following sectionswe will not spend time in formally or mathematically defining each of these entities since the scope of the book is more toward applied or practical machine learning if you consider our real-world problem from earlierone of the tasks could be predicting outages for our infrastructureexperience would be what our machine learning model would gain over time by observing patterns from various device data attributesand the performance of the model could be measured in various ways like how accurately the model predicts outages defining the taskt we had discussed briefly in the previous section about the tasktwhich can be defined in two-fold approach from problem standpointthe tasktis basically the real-world problem to be solved at handwhich could be anything from finding the best marketing or product mix to predicting infrastructure failures in the machine learning worldit is best if you can define the task as concretely as possible such that you talk about what the exact problem is which you are planning to solve and how you could define or formulate the problem into specific machine learning task machine learning based tasks are difficult to solve by conventional and traditional programming approaches tasktcan usually be defined as machine learning task based on the process or workflow that the system should follow to operate on data points or samples typically data sample or point will consist of multiple data attributes (also called features in machine learning lingojust like the various device parameters we mentioned in our problem for dss company earlier typical data point can be