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2836926
Deep Learning (Adaptive Computation and Machine Learning series)
87% of respondents would recommend this to a friend
Nº de artículo:
2836926
CLP 73067
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What Stands Out
Comprehensive Coverage
This book offers an in-depth exploration of deep learning principles and techniques, catering to both beginners and advanced practitioners, ensuring a solid foundation in adaptive computation.
Practical Applications
Focuses on real-world applications of deep learning, illustrating how theories translate into practice, thus solving complex problems across various industries effectively.
Expert Insights
Authored by leading experts in the field, providing readers with authoritative knowledge and cutting-edge advancements in machine learning, enhancing their understanding and skills.
Detalles de producto
| Package Weight | 3 Pound |
Who Should Buy?
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Aspiring Data Scientists
Ideal for individuals starting their journey in machine learning, providing foundational knowledge in deep learning techniques.
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Academic Researchers
Useful for researchers in AI and machine learning fields, offering advanced insights and methodologies in deep learning.
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Industry Professionals
Benefits professionals seeking to apply deep learning in real-world applications, enhancing existing skills and knowledge.
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Beginner Programmers
Not suitable for those with limited programming experience, as it requires a basic understanding of coding and algorithms.
DESCRIPCIÓN DEL PRODUCTO
Deep Learning (Adaptive Computation and Machine Learning series)
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Intelligence & Semantics Editorial Review
Deep Learning (Adaptive Computation and Machine Learning series) offers a comprehensive and rigorous insight into deep learning from renowned experts. It serves as an invaluable reference for students, researchers, and practitioners, striking a perfect balance between theory and practical considerations. The book delves into various network types like multi-layer perceptrons and convolutional neural networks while also discussing applications in real-world scenarios. Comprehensive analysis is provided on fundamental concepts such as linear algebra and optimization, making it suitable for those with a solid background in machine learning. However, it’s worth noting that this work is tailored more for individuals familiar with deep learning principles, ensuring readers grasp advanced insights effectively.
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ventajas
- In-depth exploration of deep learning concepts and practices
- Ideal for students and researchers in machine learning
- Covers advanced topics and current research trends
- Strong foundation in linear algebra and statistics
- Excellent resource for those advancing in deep learning
Contras
- Assumes prior knowledge of deep learning fundamentals
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CLP 73067
Haz tu pedido ahora y recíbelo por ahí Martes, Noviembre 24
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