The book begins with an overview of the different types of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. The authors then discuss the various data processing techniques that are essential for machine learning, such as data cleaning, feature engineering, and model selection.In the following chapters, the book covers a wide range of machine learning topics, including:Regression: A technique for predicting continuous target values.Classification: A technique for predicting categorical target values.Clustering: A technique for grouping similar data points together.Dimensionality reduction: A technique for reducing the number of features in a dataset.Model evaluation: A technique for assessing the performance of a machine learning model.The book also includes a chapter on deep learning, which is a subfield of machine learning that has gained popularity in recent years.
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Dr. Lilly Sheeba S, Ms. Kavitha Duraipandian and Ms. Sivasankari.K are currently working in the Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram Campus, Chennai.
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The book begins with an overview of the different types of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. The authors then discuss the various data processing techniques that are essential for . Bestandsnummer des Verkäufers 1311648402
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book begins with an overview of the different types of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning. The authors then discuss the various data processing techniques that are essential for machine learning, such as data cleaning, feature engineering, and model selection.In the following chapters, the book covers a wide range of machine learning topics, including:Regression: A technique for predicting continuous target values.Classification: A technique for predicting categorical target values.Clustering: A technique for grouping similar data points together.Dimensionality reduction: A technique for reducing the number of features in a dataset.Model evaluation: A technique for assessing the performance of a machine learning model.The book also includes a chapter on deep learning, which is a subfield of machine learning that has gained popularity in recent years.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch. Bestandsnummer des Verkäufers 9786207448760
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