Machine Learning: A Probabilistic Perspective

Released on by Sweta
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  • Machine Learning: A Probabilistic Perspective Book Detail

  • Author : Sweta
  • Release Date : 2023-03-21
  • Publisher : AG PUBLISHING HOUSE (AGPH Books)
  • Genre : Study Aids
  • Pages : 220
  • ISBN 13 : 8119152212
  • File Size : 55,55 MB
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Machine Learning: A Probabilistic Perspective by Sweta PDF Summary

Book Description: Machine learning (ML) is a subfield of AI that allows computers to "learn" from the data and improve over time without being explicitly programmed. Algorithms that use machine learning may analyze data for patterns and use that knowledge to generate predictions. To sum up, machine learning algorithms & models acquire knowledge from previous data. Traditional programming entails a computer engineer crafting a set of rules that tell a computer how to take raw data and produce a certain result. Most commands follow an IF-THEN format: the computer acts only if the specified condition holds. The opposite is true with machine learning, which is the automated process that allows computers to solve issues with little or no human intervention and to respond following what they have learned from previous experiences. The terms "artificial intelligence" & "machine learning" are often used interchangeably, although they refer to two distinct processes. Machine learning is a branch of artificial intelligence that allows intelligent systems to autonomously learn new things from data, while artificial intelligence as a whole refers to robots that can make choices, acquire new skills, and solve problems. You may train machine learning algorithms to conduct computations, process data, and recognize patterns without explicitly programming them to do so by providing them with samples of labeled data.

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