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Machine Learning & Deep Learning
Core ML/DL concepts: supervised and unsupervised learning, neural networks (CNN, RNN/LSTM, GAN, Transformers), training techniques, model optimization, and real-world applications in software engineering and NLP.
Transformers & Attention Mechanisms
Self-attention, multi-head attention, positional encoding, BERT (encoder-only), GPT (decoder-only), transfer learning, and applications (NLP, code generation).
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