Ian Goodfellow Yoshua Bengio Aaron Courville Deep Learning MIT Press Book
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Ian Goodfellow Yoshua Bengio Aaron Courville Deep Learning MIT Press Book
Authored by Ian Goodfellow, Yoshua Bengio, and Aaron Courville as part of the Adaptive Computation and Machine Learning Series, Deep Learning operates as an instructional reference centered on neural networks, deep learning, and artificial intelligence tech. This publication investigates the theoretical bases and practical ideas that sustain current machine learning frameworks.
The text examines primary rules tied to machine learning, neural net building, tuning methods, and data processing procedures. The content is structured to supply readers with an organized grasp of deep learning models along with the mathematical principles that back their creation and usage.
Users can study subjects linked to deep artificial neural nets, feature representation, convolutional networks, sequential forecasting, and machine learning layouts. The volume also covers methods applied in artificial intelligence inquiry, data-driven frameworks, and advanced computational learning tools.
Aimed at learners, scholars, instructors, and IT specialists, this text delivers broad coverage of deep learning notions applied over artificial intelligence, data science, vision processing, and language technology domains.
Topics Covered
- Deep learning fundamentals
- Neural network architectures
- Machine learning principles
- Optimization algorithms
- Deep neural network training
- Representation learning
- Convolutional neural networks
- Sequence modeling concepts
- Artificial intelligence applications
- Computational learning methods
Product Details
- Author: Ian Goodfellow; Yoshua Bengio; Aaron Courville
- ISBN-13: 9780262035613
- ISBN-10: 0262035618
- Series: Adaptive Computation and Machine Learning
- Title: Deep Learning
- Language: English
- Category: Artificial Intelligence
- Subject: Deep Learning and Machine Learning
Product Type
Artificial Intelligence