AI and LLM

Supervised learning

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Unsupervised learning

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Classification vs regression

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Regression target

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Overfitting

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Underfitting

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Train/test split

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Cross validation

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Bias-variance

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Regularization

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Feature scaling

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Confusion matrix

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Precision

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Recall

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F1 score

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Accuracy pitfall

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Gradient descent

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Learning rate

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Loss function

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Linear regression

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Logistic regression

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Decision tree

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Random forest

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kNN

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K-means

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SVM

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PCA

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Gradient boosting

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Neural network

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Activation function

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ReLU

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Backpropagation

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CNN use

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RNN use

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Dropout

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Epoch

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Batch size

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Vanishing gradient

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Transfer learning

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What is an LLM

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Transformer

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Attention

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Token

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Context window

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Temperature

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Hallucination

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Fine-tuning

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Prompt engineering

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Few-shot

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Chain of thought

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RAG

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Embeddings

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Vector database

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System prompt

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Grounding

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Guardrails

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Agent

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Function calling

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Evaluation

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Diffusion model

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