Machine Learning and Data Science

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Data science is a branch of computer science that deals in the extraction of valuable insights from vast datasets through a combination of disciplines such as mathematics, ML, statistics, and data engineering.

Big data and data science are set to bring in a digital revolution with groundbreaking technologies like artificial intelligence (AI), machine learning (ML), and deep learning. The essence of data science is to dive into massive datasets to extract meaningful information from them.

The fields of data science, AI, and ML are intrinsically linked to one another. While artificial intelligence is a broad umbrella that includes a wide range of applications, right from text analysis to robotics, machine learning, is a subset of artificial intelligence that focuses on training machines how to ‘learn’ via advanced algorithms and perform specific tasks while simultaneously improving performance through experience.

Machine learning supports data science by providing a suit of algorithms for data modeling/ analysis (through training of machine learning algorithms), decision making (through streaming, online learning, real-time testing that are all topics that come under machine learning), and even data preparation (machine learning algorithms automatically detect anomalies in the data). Machine learning is the branch of AI that works best with data science. Data Science stitches together a bunch of ideas/ algorithms drawn from machine learning to create a solution.   Data scientists leverage AI and ML to develop smart machines which can process, analyze, and interpret vast datasets much faster than ever.