figure - traditional programming paradigm from figure - you can get the idea that the core inputs that are given to the computer are data and one or more programs that are basically code written with the help of programming languagesuch as high-level languages like javapythonor low-level like or even assembly programs enable computers to work on dataperform computationsand generate output task that can be performed really well with traditional programming paradigms is computing your annual tax nowlet' think about the real-world infrastructure problem we discussed in the previous section for dss company do you think traditional programming approach might be able to solve this problemwellit could to some extent we might be able to tap in to the device data and event streams and logs and access various device attributes like usage levelssignal strengthincoming and outgoing connectionsmemory and processor usage levelserror logs and eventsand so on we could then use the domain knowledge of our network and infrastructure experts in our teams and set up some event monitoring systems based on specific decisions and rules based on these data attributes this would give us what we could call as rule-based reactive analytical solution where we can monitor devicesobserve if any specific anomalies or outages occurand then take necessary action to quickly resolve any potential issues we might also have to hire some support and operations staff to continuously monitor and resolve issues as needed howeverthere is still pressing problem of trying to prevent as many outages or issues as possible before they actually take place can machine learning help us in some waywhy machine learningwe will now address the question that started this discussion of why we need machine learning considering what you have learned so farwhile the traditional programming paradigm is quite good and human intelligence and domain expertise is definitely an important factor in making data-driven decisionswe need machine learning to make faster and better decisions the machine learning paradigm tries to take into account data and expected outputs or results if any and uses the computer to build the programwhich is also known as model this program or model can then be used in the future to make necessary decisions and give expected outputs from new inputs figure - shows how the machine learning paradigm is similar yet different from traditional programming paradigms