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Machine Learning. Supervised and unsupervised learning, latent semantic indexing, spectral clustering and Bellman equations

Über Machine Learning. Supervised and unsupervised learning, latent semantic indexing, spectral clustering and Bellman equations

Document from the year 2022 in the subject Computer Sciences - Artificial Intelligence, grade: B.Tech, Amity University (Amity School of Engineering and Technology), language: English, abstract: The study material of Machine Learning is designed mainly for the students of engineering graduates. The syllabus is taken from Guru Gobind Singh Indraprastha University Delhi. It covers mainly all the topics of the subjects. The course is designed in a simple and precise manner. For complete knowledge and more study about the subject, students are advised to follow the books referred to in the references. Machine learning is a subfield of computer science, but is often also referred to as predictive analytics, or predictive modeling. Its goal and usage is to build new and/or leverage existing algorithms to learn from data, in order to build generalizable models that give accurate predictions, or to find patterns, particularly with new and unseen similar data.

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  • Sprache:
  • Englisch
  • ISBN:
  • 9783346792129
  • Einband:
  • Taschenbuch
  • Seitenzahl:
  • 196
  • Veröffentlicht:
  • 28. Dezember 2022
  • Ausgabe:
  • 22001
  • Abmessungen:
  • 148x14x210 mm.
  • Gewicht:
  • 292 g.
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Beschreibung von Machine Learning. Supervised and unsupervised learning, latent semantic indexing, spectral clustering and Bellman equations

Document from the year 2022 in the subject Computer Sciences - Artificial Intelligence, grade: B.Tech, Amity University (Amity School of Engineering and Technology), language: English, abstract: The study material of Machine Learning is designed mainly for the students of engineering graduates. The syllabus is taken from Guru Gobind Singh Indraprastha University Delhi. It covers mainly all the topics of the subjects. The course is designed in a simple and precise manner. For complete knowledge and more study about the subject, students are advised to follow the books referred to in the references.
Machine learning is a subfield of computer science, but is often also referred to as predictive analytics, or predictive modeling. Its goal and usage is to build new and/or leverage existing algorithms to learn from data, in order to build generalizable models that give accurate predictions, or to find patterns, particularly with new and unseen similar data.

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