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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.
Machine Learning Fundamentals
ML definition, types of learning (supervised, unsupervised, semi-supervised, reinforcement), bias-variance tradeoff, overfitting, cross-validation, and evaluation metrics.
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