datawhalechina/leedl-tutorial

Features

• Deep Learning Education - Provides a comprehensive set of curated resources for learning neural network theory and practice.
• Deep Learning Tutorials - Offers instructional resources and modular tutorials specifically covering deep learning architectures and frameworks.
• Deep Learning Study Guides - Provides a structured technical study guide with conceptual explanations and proofs for deep learning equations.
• AI Curriculum Materials - Provides a complete set of slides, notes, and assignments designed to teach AI architectures.
• Deep Learning Courses - Serves as a comprehensive educational course covering neural network architectures and deep learning fundamentals.
• Deep Learning Fundamentals - Delivers structured educational content on the core concepts of neural networks and generative models.
• Mathematical Formula Derivations - Provides detailed step-by-step mathematical proofs to explain the underlying logic of deep learning models.
• Applied Technical Exercises - Ships structured assignments that integrate code and video to bridge theory and practice.
• Technical Skill Training - Bridges the gap between theoretical deep learning and practical implementation through hands-on exercises.
• Artificial Intelligence Research - Covers advanced artificial intelligence research trends including self-supervised learning and adversarial attacks.
• Deep Learning Architectures - Explains the structural composition and functions of common deep learning network architectures.
• Advanced Research Topics - Includes specialized tutorials on advanced research areas such as self-supervised learning and adversarial attacks.
• Offline Learning Materials - Provides curated notes and portable documents optimized for technical study without an internet connection.
• Offline Learning Resources - Enables the study of complex machine learning material through offline-accessible documentation and notes.

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