Artikel #:
195936580
Applied Machine Learning with Scikit-Learn, Keras and TensorFlow; Concepts, Tools and Techniques for Developing Intelligent Systems (Cover may vary)
Artikel #:
195936580
€ 77
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Naročite zdaj in dobite okoli dne: Sobota, Avgust 15
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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.
Podrobnosti produkta
| Publishers | Iceberg Publishing House |
| Date of publication | 17 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 |
| Item Weight | 1.5 lbs (680 grams) |
Who Should Buy?
-
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.
-
Complete Beginners
Not suitable for absolute beginners, as prior knowledge of programming and data science concepts is necessary to follow along.
OPIS IZDELKA
Applied Machine Learning with Scikit-Learn, Keras and TensorFlow; Concepts, Tools and Techniques for Developing Intelligent Systems (Cover may vary)
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Prednosti
- Comprehensive coverage of topics
- User-friendly examples
- Supports practical learning
- Great for beginners and experts
- Up-to-date with latest tools
Slabosti
- Some advanced topics may need prior knowledge.
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