Item #:
87943410
Python machine learning programming ［PyTorch&scikit-learn edition］ impress top gear Tankobon Softcover – December 15, 2022
95% of respondents would recommend this to a friend
Item #:
87943410
SAR 162
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This book is irreplaceable, both as an overview of the ambitious field of machine learning and as a treasure trove of practical knowledge.
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What Stands Out
Comprehensive Learning
Offers in-depth coverage of Python machine learning techniques, including practical applications with PyTorch and scikit-learn, catering to both beginners and advanced learners.
Hands-On Approach
Includes numerous coding examples and projects that enhance understanding and encourage practical application of machine learning concepts in real-world scenarios.
Updated Content
Published in December 2022, providing the latest insights and developments in machine learning technologies, ensuring readers are equipped with current and relevant knowledge.
Product Details
| Item Weight | 1 lbs (450 grams) |
Who Should Buy?
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Beginner Data Scientists
Ideal for newcomers wishing to grasp machine learning concepts using Python libraries like PyTorch and scikit-learn.
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Students and Learners
Perfect for academic use, excellent for students needing a comprehensive guide for projects and coursework in machine learning.
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Professionals Upskilling
Beneficial for professionals seeking to enhance their skills in Python programming and machine learning techniques.
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Advanced Practitioners
Not suitable for experts who require in-depth analysis or advanced techniques beyond the foundational concepts covered.
Product Description
Python machine learning programming ［PyTorch&scikit-learn edition］ impress top gear Tankobon Softcover – December 15, 2022
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Pros
- Comprehensive learning materials
- User-friendly interface
- Strong community support
- Hands-on practical exercises
- Covers popular libraries
Cons
- Some advanced topics may be brief.
Product Price History
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SAR 162
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Features & Benefits
- Comprehensive guide covering basics to advanced machine learning techniques.
- In-depth explanations of scikit-learn and PyTorch for practical applications.
- Explores cutting-edge methods like Transformers and graph neural networks.
- Features hyperparameter tuning, ensemble learning, and regression analysis.
- Includes practical coding examples for real-world applications.
- Highly recommended by readers and industry experts for effective learning.
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