Learn AI / ML

60 cards · 4 levels · spaced repetition · notes · quizzes

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1
Foundations
Paradigms, linear & logistic models, trees, SVM, k-means, gradient descent, overfitting, metrics
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2
Core Architectures
Neurons, activations, optimizers, CNNs, ResNets, RNNs, attention, transformers, ViT, GNNs
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3
Language Models
Tokenization, embeddings, LLM training, architectures, MoE, distillation, sampling, fine-tuning
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4
Advanced & Applied
Diffusion, RLHF, RAG, agents, LoRA, quantization, MLOps, speech, synthetic data, ethics
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