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Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition
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Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.
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Detalji o proizvodu
- Third edition of the bestselling Python machine learning book
- Clear and intuitive explanations of machine learning techniques
- Updated and expanded for TensorFlow 2, GANs, and reinforcement learning
- Covers scikit-learn, TensorFlow, and PyTorch frameworks
- Includes practical examples for image classification, sentiment analysis, and more
- Suitable for beginners and intermediate readers
| Publisher | Packt Publishing |
| Publication date | 12 Dec. 2019 |
| Edition | 3rd Revised edition |
| Language | English |
| Print length | 770 pages |
| ISBN-10 | 1789955750 |
| ISBN-13 | 978-1789955750 |
| Item weight | 1.3 kg |
| Dimensions | 19.05 x 4.42 x 23.5 cm |
Who Should Buy?
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Aspiring Data Scientists
Ideal for beginners looking to understand machine learning fundamentals and build a solid foundation in Python.
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Software Developers
Great for developers wanting to integrate machine learning capabilities into existing applications using Python libraries.
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Students and Educators
Suitable for academic purposes, providing clear explanations and practical examples for coursework or research.
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Complete Beginners
Not suitable for those with no programming background, as some prior knowledge of Python is recommended.
OPIS PROIZVODA
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AI & Machine Learning Editorial Review
Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition is a comprehensive resource for both aspiring data scientists and those looking to deepen their understanding of machine learning. The book, published by Packt Publishing, spans 770 pages and offers extensive coverage of TensorFlow 2.0, making it ideal for readers with technical backgrounds in fields like computer science and mathematics. While many find it a valuable reference, beginners may encounter challenges with the required coding environment, which can complicate the learning experience. However, the structured approach to complex concepts is highly praised.
Customer Reviews & Ratings
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5 zvijezda
68%
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4 zvijezda
21%
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3 zvijezda
6%
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2 zvijezda
2%
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1 zvijezda
3%
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Pros
- Extensive coverage of TensorFlow 2.0
- Helpful for refreshing knowledge
- Well-structured progression of topics
- Excellent for junior data scientists
- Technical details clearly explained
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Karakteristike i prednosti
- Comprehensive guide to machine learning and deep learning with Python
- Covers all the essential machine learning techniques in depth
- Introduces readers to TensorFlow 2.0 and latest additions to scikit-learn
- Explores cutting-edge reinforcement learning techniques based on deep learning
- Ideal for developers and data scientists who want to create practical machine learning and deep learning code
- Teaches principles behind machine learning, allowing you to build models and applications for yourself
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