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Dive into Deep Learning

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About

Dive into Deep Learning is a comprehensive resource for deep learning enthusiasts and practitioners that merges theory with practical implementations. It covers a variety of topics within deep learning including neural networks for regression and classification, convolutional neural networks, recurrent neural networks, attention mechanisms, optimization algorithms, and various applications in computer vision and natural language processing. The book is designed with interactive Jupyter notebooks that allow users to modify code and experiment with deep learning concepts. It is supported by a vast community for discussions and learning, and is used in over 500 universities globally. Offering a range of implementations in popular frameworks such as PyTorch, MXNet, TensorFlow, and JAX, this resource stands out for providing both theoretical knowledge and hands-on experience in deep learning. The book is available online and can be utilized in platforms like Google Colab and Amazon SageMaker, making it accessible for hands-on learners.

Platform

Keywords

nlp deep learning interactive learning computer vision neural networks

Task

learning resources

Features

• supports community engagement

• focus on both theory and practical applications

• used in over 500 universities worldwide

• adopts various deep learning frameworks

• covers multiple deep learning topics

• interactive learning with jupyter notebooks

Pricing Plans

Free

• Interactive Jupyter Notebooks

• Access to Community Discussions

• Comprehensive Learning Materials

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