Fundamentals Machine Learning Algorithms by Chitra Mrs (9 results)
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Taschenbuch. Condition: Neu. Fundamentals of Machine Learning Algorithms | Mrs M. G. Chitra (u. a.) | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207483556 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | A…nbieter: preigu.
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Published by LAP LAMBERT Academic Publishing Feb 2026, 2026
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 60 pp. Englisch.
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Published by LAP LAMBERT Academic Publishing Apr 2024, 2024
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 60 pp. Englisch.
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Published by LAP LAMBERT Academic Publishing Feb 2026, 2026
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In machine learning, models and algorithms can learn from data and make predictions or judgments without explicit programming are developed. Machine learning is a subfield of artificial intelligence (AI). Machine learning uses a wide ra…nge of important algorithms and techniques. A list of machine learning algorithms is shown below: Support Vector Machine Algorithm, Decision Tree Classification Algorithm, Random Forest Algorithm, Logistic Regression Algorithm, Linear Regression Algorithm, K-Nearest Neighbor (KNN) Algorithm, Naïve Bayes Classifier Algorithm, K-Means Clustering Algorithm, XG-Boost Algorithm. These algorithms are employed in many different areas, such as robotics, marketing, healthcare, and finance, and they form the foundation of machine learning. The choice of algorithm is influenced by the nature of the problem, the characteristics of the data, and the available computing capacity.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.
Language: English
Published by LAP LAMBERT Academic Publishing Apr 2024, 2024
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In machine learning, models and algorithms can learn from data and make predictions or judgments without explicit programming are developed. Machine learning is a subfield of artificial intelligence (AI). Machine learning uses a wide ra…nge of important algorithms and techniques. A list of machine learning algorithms is shown below: Support Vector Machine Algorithm, Decision Tree Classification Algorithm, Random Forest Algorithm, Logistic Regression Algorithm, Linear Regression Algorithm, K-Nearest Neighbor (KNN) Algorithm, Naïve Bayes Classifier Algorithm, K-Means Clustering Algorithm, XG-Boost Algorithm. These algorithms are employed in many different areas, such as robotics, marketing, healthcare, and finance, and they form the foundation of machine learning. The choice of algorithm is influenced by the nature of the problem, the characteristics of the data, and the available computing capacity.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In machine learning, models and algorithms can learn from data and make predictions or judgments without explicit programming are developed. Machine learning is a subfield of artificial intelligence (AI). Machine learning uses a wide ran…ge of important algorithms and techniques. A list of machine learning algorithms is shown below: Support Vector Machine Algorithm, Decision Tree Classification Algorithm, Random Forest Algorithm, Logistic Regression Algorithm, Linear Regression Algorithm, K-Nearest Neighbor (KNN) Algorithm, Naïve Bayes Classifier Algorithm, K-Means Clustering Algorithm, XG-Boost Algorithm. These algorithms are employed in many different areas, such as robotics, marketing, healthcare, and finance, and they form the foundation of machine learning. The choice of algorithm is influenced by the nature of the problem, the characteristics of the data, and the available computing capacity.
