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Neural networks, training loops, and modern representation learning.
Understand layers, activations, and optimization basics.
Learn how training and inference differ in practice.
Recognize the building blocks behind transformer models.
Prepare for LLM and multimodal learning paths.
Architecture essentials
Optimization and regularization
Core deep learning structures
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Back to LearnPractical examples that connect the category to real-world implementation.
Real-time thermal imaging analysis with computer vision and predictive models
Useful starting points and supporting materials for this category.