Role of Machine Learning in Data Science


  • Machine learning is used in data science for data analysis and extracting valuable insights from data.
  • Artificial Intelligence and machine learning are ruling the market. They obscure all facets of data science, including business intelligence and data analytics.

Machine Learning has been around for a very long time and has been existing even before we came to realize it. Machine learning has altered how data extraction and interpretation are performed via automatic sets of general procedures.

Machine learning is one of the many domains covered by data science. Data science consists of many fields and techniques, such as statistics, Artificial Intelligence (AI), to draw meaningful insights. While analysts derived insights from their firm’s data, data scientists used data to generate algorithms, AI and machine learning models. The former focused more on addressing bigger business challenges, and the latter strived to solve particular problems. But things have changed now. What’s gaining traction today is the capability to apply mathematical calculations to big data quickly and automatically.

Together, data science and machine learning are working hand-in-hand to revolutionize how we live and are working toward a single goal: Discovering new insights to help businesses grow. Today, businesses want to derive maximum value from data, and the fusion of analytics and data science allows them to gain a more comprehensive perspective of their organization.

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