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Hands-on exercises and resources designed to bridge the gap between theoretical knowledge and practical implementation.
Distinguishing note: Focuses on the acquisition of practical skills through exercises, distinct from passive learning.
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LLM101n is an educational machine learning curriculum and open-source resource designed to teach the fundamental principles and practical implementation of large language models. It functions as a technical manual that guides users through the end-to-end process of building and training neural network architectures from scratch using a dynamic tensor library for automatic differentiation and GPU-accelerated computation. The project distinguishes itself through interactive, notebook-based instruction that allows for real-time visualization of training processes. It supports rapid experimentati
Bridges the gap between theory and implementation through hands-on deep learning exercises.