Data Science VS Machine Learning

Data Science VS Machine Learning
Written by Sagar RabidasNovember 30, 2021
4 min read
Machine Learning
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Sagar Rabidas

Software Developer

Today we discuss some differences between Data Science and Machine Learning.

Machine Learning

Machine learning is an application of Artificial Intelligence (AI) that gives systems the potential to routinely examine and enhance from experience without being explicitly programmed. Machine studying makes a specialty of the development of pc programs that can get admission to records and use it to study for themselves.

The process of learning begins with observations or statistics, together with examples, direct revel in, or training, to look for patterns in statistics and make better choices in the future primarily based on the examples that we provide. The number one intention is to allow the computers to examine mechanically without human intervention or help and modify movements consequently.

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Data Science

Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data science practitioners apply machine learning algorithms to numbers, text, images, video, audio, and more to produce artificial intelligence (AI) systems to perform tasks that ordinarily require human intelligence. In turn, these systems generate insights that analysts and business users can translate into tangible business value.

Data scientists are specialists who excel in converting raw data into critical business matters. These scientists are skilled in algorithmic coding along with concepts like data mining, machine learning, and statistics. Data science is used extensively by companies like Amazon, Netflix, the healthcare sector, in the fraud detection sector, internet search, airlines, etc.

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Difference between Data Science and Machine Learning

Data Science

  • Data Science is a field about processes and systems to extract data from structured and semi-structured data.
  • Need the entire analytics universe.
  • Branch that deals with data.
  • Data in Data Science maybe or maybe not have evolved from a machine or mechanical process.
  • Data Science as a broader term not only focuses on algorithms statistics but also takes care of data processing.
  • It is a broad term for multiple disciplines.
  • Many operations of data science that is, data gathering, data cleaning, data manipulation, etc.
  • Example: Netflix uses Data Science technology.

Machine Learning

  • Machine Learning is a field of study that gives computers the capability to learn without being explicitly programmed.
  • Combination of Machine and Data Science.
  • Machines utilize data science techniques to learn about the data.
  • It uses various techniques like regression and supervised clustering.
  • But it is only focused on algorithm statistics.
  • It fits within data science.
  • It is three types: Unsupervised learning, Reinforcement learning, Supervised learning.
  • Example: Facebook uses Machine Learning technology.
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DS vs ML
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Sagar Rabidas
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made with by Abhishek & Priyanka Jalan