Applied Machine Learning with Scikit-Learn, Keras and TensorFlow; Concepts, Tools and Techniques for Developing Intelligent Systems (Cover may vary)
Item #: 195936580

Applied Machine Learning with Scikit-Learn, Keras and TensorFlow; Concepts, Tools and Techniques for Developing Intelligent Systems (Cover may vary)

Item #: 195936580

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What Stands Out

Comprehensive Coverage
This book offers an extensive exploration of machine learning concepts, covering Scikit-Learn, Keras, and TensorFlow, ensuring readers gain a well-rounded understanding of developing intelligent systems.
Hands-On Approach
Packed with practical examples and real-world applications, this resource allows readers to apply machine learning techniques immediately, enhancing learning and skills development through engaging, hands-on projects.
Expert Insights
Authored by industry professionals, the book shares invaluable insights and best practices, helping readers avoid common pitfalls and effectively design and implement machine learning models.

Product Details

Shop Applied Machine Learning with Scikit-Learn, Keras and TensorFlow; Concepts, Tools and Techniques for Developing Intelligent Systems (Cover may vary) online at a best price in São Tomé and Príncipe. 6050624828
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PublishersIceberg Publishing House
Date of publicization17 August 2021
Language Turkish
Print length 896 pages
ISBN-10 6050624828
ISBN-13 978-6050624823
Dimensions 20.8 x 1.8 x 13.8 cm

Who Should Buy?

Suitable For
  • Aspiring Data Scientists

    Ideal for individuals wanting to build a foundational knowledge in machine learning and practical skills using popular libraries.

  • Software Developers

    Great for developers seeking to implement machine learning techniques into existing applications and systems using Python.

  • Machine Learning Instructors

    Beneficial for educators who require structured content and examples to effectively teach machine learning concepts to students.

Not Suitable For
  • Complete Beginners

    Not suitable for absolute beginners, as prior knowledge of programming and data science concepts is necessary to follow along.

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Pros

  • Comprehensive coverage of topics
  • User-friendly examples
  • Supports practical learning
  • Great for beginners and experts
  • Up-to-date with latest tools

Cons

  • Some advanced topics may need prior knowledge.

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