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How Exactly Is Data Science Beyond Machine Learning?
Data-driven analytics, i.e., Data Science, is in use across various sectors for many decades whereas, Machine Learning is an advanced concept in analytics that is receiving a lot of hype for the past five years. The rapid advancements in these technologies have transformed the way enterprises across different industries function. At present, there is an exclusively high demand for the skilled Data Science & Machine Learning professionals who are very much capable of handling all the real-world analytics industry challenges to perfection.
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We are aware of the differences between Machine Learning & AI. Now, in this post, let’s understand how Data Science is beyond Machine Learning.
Data Science Beyond Just Machine Learning-
Speaking of Data Science & Machine Learning technologies, the major feature that sets them apart is that the process of Data science is more of a generalist approach, whereas Machine Learning is a specialist approach.
As a part of their job-role, Data Scientists need to explore the insights from the data & communicate the findings to a non-technical audience. These analytics experts have nowadays become a crucial part of the enterprise’s software development process.
While coming to the job role of a Machine Learning Engineer, they need to build new tools that support Data Scientists in the execution of their data analytics operations. These professionals are very skilled in handling advanced Machine Learning algorithms to help Data Scientists in their data modeling techniques to achieve the desired objectives.
Another distinct feature that sets these two technologies apart from each other is that Machine Learning capabilities can be scaled up high by increasing the number of resources, but Data Science operations cannot be scaled up by simply increasing the number of Data Scientists.
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