ThinamXx/300Days__MachineLearningDeepLearning

Covers 40+ implementation notebooks spanning CNNs, RNNs, GANs, attention mechanisms, and transformer architectures using PyTorch and Fastai. Projects progress from foundational algorithms (logistic regression, LeNet) through advanced applications including sentiment analysis, natural language inference with BERT, medical imaging classification, and collaborative filtering. Structured around canonical textbooks (Hands-On ML, Deep Learning with PyTorch, Dive into Deep Learning) with systematic coverage of computer vision, NLP, and neural network theory alongside practical evaluation metrics and data preprocessing techniques.

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