9786207483556 - Fundamentals of Machine Learning Algorithms di CHITRA, Mrs M.G.; GOVINDARAJ, Dr. RAMYA (7 risultati)

Condizione: New.

Taschenbuch. Condizione: 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: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Condizione: New. Print on Demand.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 60 pp. Englisch.

Condizione: New. PRINT ON DEMAND.

Taschenbuch. Condizione: 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 range 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.

Taschenbuch. Condizione: 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 range 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.