Description

Chapter 1 Overview of Artificial Intelligence and Machine Learning.- Chapter 2 Basic Knowledge of Machine Learning.- Chapter 3 Linear Regression.- Chapter 4 Logistic Regression.- Chapter 5 Model Optimization.- Chapter 6  Support Vector Machine.- Chapter 7  Decision Tree.- Chapter 8 Understanding of Decision Tree.- Chapter 9 Bayesian Analysis.- Chapter 10 Deep Learning.

Practical Machine Learning Illustrated with KNIME

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Hardback by Yu Geng

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Chapter 1 Overview of Artificial Intelligence and Machine Learning.- Chapter 2 Basic Knowledge of Machine Learning.- Chapter 3 Linear Regression.-... Read more

    Publisher: Springer
    Publication Date: 8/30/2024
    ISBN13: 9789819739530, 978-9819739530
    ISBN10: 9819739535

    Non Fiction , Computing

    Description

    Chapter 1 Overview of Artificial Intelligence and Machine Learning.- Chapter 2 Basic Knowledge of Machine Learning.- Chapter 3 Linear Regression.- Chapter 4 Logistic Regression.- Chapter 5 Model Optimization.- Chapter 6  Support Vector Machine.- Chapter 7  Decision Tree.- Chapter 8 Understanding of Decision Tree.- Chapter 9 Bayesian Analysis.- Chapter 10 Deep Learning.

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