Description

Book Synopsis

Machine Learning: Concepts, Techniques and Applications starts at basic conceptual level of explaining machine learning and goes on to explain the basis of machine learning algorithms. The mathematical foundations required are outlined along with their associations to machine learning. The book then goes on to describe important machine learning algorithms along with appropriate use cases. This approach enables the readers to explore the applicability of each algorithm by understanding the differences between them. A comprehensive account of various aspects of ethical machine learning has been discussed. An outline of deep learning models is also included. The use cases, self-assessments, exercises, activities, numerical problems, and projects associated with each chapter aims to concretize the understanding.

Features

  • Concepts of Machine learning from basics to algorithms to implementation

  • Comparison

    Table of Contents

    1. Introduction. 2. Understanding Machine Learning. 3. Mathematiccal Foundations and Machine Learning. 4. Foundations and categoris of Machine Learning Techniques. 5. Machine Learning: Tool and Software 6. Classification Algorithms. 7. Probabilistic and Regression based approaches. 8. Performance Evaluation & Ensemble Methods. 9. Unsupervised Learning. 10. Sequence Models. 11. Reinforcement Learning. 12. Machine Learning Applications – Approaches. 13. Domain based Machine Learning Applications. 14. Ethical Aspects of Machine Learning. 15. Introduction to Deep Learning and Convolutional Neural Networks. 16. Other Models of Deep Learning and Applications of Deep Learning.

Machine Learning

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£133.00

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RRP £140.00 – you save £7.00 (5%)

Order before 4pm today for delivery by Mon 26 Jan 2026.

A Hardback by S Sendhilkumar, S Sendhilkumar

15 in stock


    View other formats and editions of Machine Learning by S Sendhilkumar

    Publisher: Taylor & Francis Ltd
    Publication Date: 5/17/2023 12:00:00 AM
    ISBN13: 9781032268286, 978-1032268286
    ISBN10: 103226828X
    Also in:
    Machine learning

    Description

    Book Synopsis

    Machine Learning: Concepts, Techniques and Applications starts at basic conceptual level of explaining machine learning and goes on to explain the basis of machine learning algorithms. The mathematical foundations required are outlined along with their associations to machine learning. The book then goes on to describe important machine learning algorithms along with appropriate use cases. This approach enables the readers to explore the applicability of each algorithm by understanding the differences between them. A comprehensive account of various aspects of ethical machine learning has been discussed. An outline of deep learning models is also included. The use cases, self-assessments, exercises, activities, numerical problems, and projects associated with each chapter aims to concretize the understanding.

    Features

    • Concepts of Machine learning from basics to algorithms to implementation

    • Comparison

      Table of Contents

      1. Introduction. 2. Understanding Machine Learning. 3. Mathematiccal Foundations and Machine Learning. 4. Foundations and categoris of Machine Learning Techniques. 5. Machine Learning: Tool and Software 6. Classification Algorithms. 7. Probabilistic and Regression based approaches. 8. Performance Evaluation & Ensemble Methods. 9. Unsupervised Learning. 10. Sequence Models. 11. Reinforcement Learning. 12. Machine Learning Applications – Approaches. 13. Domain based Machine Learning Applications. 14. Ethical Aspects of Machine Learning. 15. Introduction to Deep Learning and Convolutional Neural Networks. 16. Other Models of Deep Learning and Applications of Deep Learning.

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