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Showing posts with the label Sony Kumari

Scope of Data Science

  Data science is the study of data to extract meaningful insights for business. It is a multidisciplinary approach that merges principles and practices from the fields of mathematics, artificial intelligence, statistics, and computer engineering to analyse huge amounts of data. This analysis helps data scientists to raise and answer questions such as what happened, why it happened, what will happen, and what can be done with the results . The term Data science is not new to the world. First, it was introduced in the 1960s and it was standardised by computer professionals in the 90s. Afterward, Data Science became the process of data design, data collection, its analysis with visualization. It became popular and got a positive response in the market as it is very helpful in machine learning so helpful in prediction and analysis, specifically business analysis. As businesses and other organizations undertake digital transformation, they’re faced with an increasing surge of data that...

AI/ML is a recreation

  AI/ML is a high-end, introductory blog. It covers the precepts of machine learning through interactive tutorials and practical examples, which make it easier to see the useful applications to different businesses and industries. AI/ML stands for artificial intelligence (AI) and machine learning (ML). Artificial intelligence (AI) is the mimicking of human intelligence by machines, especially computer systems. Machine learning helps in developing that learning to make machines capable of simulating human intelligence, so AI and ML both complement each other. AI and machine learning have ushered in a new era in computer science and data processing that is rapidly transforming a wide range of industries. As businesses and other organizations undergo digital transformation, they’re faced with an increasing surge of data that is incredibly valuable and increasingly difficult to collect, process, and analyze. Why is AI or ML decisive? It’s very obvious nowadays that data is a bu...