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Zustand: New. In English.

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Zustand: New. In English.

Zustand: New. In English.

Zustand: New. In English.

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Taschenbuch. Zustand: Neu. Grundlagen der Algorithmen des maschinellen Lernens | Mrs M. G. Chitra (u. a.) | Taschenbuch | 64 S. | Deutsch | 2024 | Verlag Unser Wissen | EAN 9786207532063 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

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

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

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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 64 pp. Spanisch.

Taschenbuch. Zustand: 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. …

Taschenbuch. Zustand: 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. …

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book is intended as a reference book for engineering students in Physics field.The present book, Biophysics-I gives a vibrant scientific field where scientists from many fields including math, chemistry, physics, engineering, pharmacology, and material.…

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 64 pp. Französisch.

Taschenbuch. Zustand: 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. Zustand: 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. …

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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Chitra M. E. (Ph.D.) Mrs. T.Mrs. T. Chitra M. E. (Ph.D.). Assist. Prof.Dr. P. Tharcis M. E. Ph. D. Assoc. Prof., Dept. of Electronics and Communication Engineering, Christian College of Engineering and Technology, India.Mr. R. Ashok .…

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - En el aprendizaje automático, se desarrollan modelos y algoritmos que pueden aprender de los datos y hacer predicciones o juicios sin necesidad de programación explícita. El aprendizaje automático es un subcampo de la inteligencia artificial (IA). El aprendizaje automático utiliza una amplia gama de algoritmos y técnicas importantes. A continuación se muestra una lista de algoritmos de aprendizaje automático: Algoritmo de máquina de vectores soporte, Algoritmo de clasificación de árbol de decisión, Algoritmo de bosque aleatorio, Algoritmo de regresión logística, Algoritmo de regresión lineal, Algoritmo K-Nearest Neighbor (KNN), Algoritmo clasificador Naïve Bayes, Algoritmo de agrupación K-Means, Algoritmo XG-Boost. Estos algoritmos se emplean en muchos ámbitos diferentes, como la robótica, el marketing, la sanidad y las finanzas, y constituyen la base del aprendizaje automático. La elección del algoritmo depende de la naturaleza del problema, las características de los datos y la capacidad informática disponible.…