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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.
ML Applications in Software Engineering
Code generation (Codex, GitHub Copilot, Claude Code), bug detection (DeepFix, BugLab), code review, semantic search (CodeBERT), and test generation.
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