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Neural networks, CNNs, RNNs, transformers, backpropagation, and architecture deep dives.
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Diffusion models, LLMs, prompt engineering, RAG, agents, and creative AI applications.
Probability, statistical tests, distributions, hypothesis testing, and the math behind ML.
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