data augmentation — Dictionary of Applied Machine Learning MCP Resource
data augmentation
is one of 120 resources on the
Dictionary of Applied Machine Learning
MCP server. Connect the server and your client can attach it as context.
by client
How to attach data augmentation from your client
- Claude Code Dictionary of Applied Machine Learning Resource/data augmentation run in your project directory
- Claude Desktop Dictionary of Applied Machine Learning Resource/data augmentation ~/Library/Application Support/Claude/claude_desktop_config.json
- Cursor Dictionary of Applied Machine Learning Resource/data augmentation ~/.cursor/mcp.json
- VS Code Dictionary of Applied Machine Learning Resource/data augmentation .vscode/mcp.json
- Zed Dictionary of Applied Machine Learning Resource/data augmentation ~/.config/zed/settings.json
- Windsurf Dictionary of Applied Machine Learning Resource/data augmentation ~/.codeium/windsurf/mcp_config.json
- Cline Dictionary of Applied Machine Learning Resource/data augmentation ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
- Gemini CLI Dictionary of Applied Machine Learning Resource/data augmentation ~/.gemini/settings.json
- Grok Dictionary of Applied Machine Learning Resource/data augmentation .mcp.json (in your project root)
- ChatGPT Dictionary of Applied Machine Learning Resource/data augmentation Settings → Connectors → Advanced → Developer mode
- Claude.ai Dictionary of Applied Machine Learning Resource/data augmentation Settings → Connectors → Add custom connector
- LangChain Dictionary of Applied Machine Learning Resource/data augmentation pip install langchain-mcp-adapters
Other resources on this server
- Reading order: Wie funktioniert ChatGPT? (LLMs)
- Reading order: KI-Grundlagen
- Reading order: Erklärbare & vertrauenswürdige KI
- Reading order: KI, Recht & AI Act
- Reading order: KI in der Praxis (ML-Systeme)
- Reading order: Mathematik der KI
- accuracy
- artificial neural network (ANN)
- attention
- autoencoder
- backpropagation
- bagging
- base learner
- baseline
- binary classification
- boosting
- bootstrap
- concept activation vector (CAV)
- classification
- clustering
- confusion matrix
- convex
- correlation
- covariance matrix
- data
- data imputation
- data leakage
- data point
- dataset
- decision boundary
- decision tree
- dimensionality reduction
- distribution shift
- effective dimension
- eigenvalue
- expectation–maximization (EM)
- ensemble
- empirical risk minimization (ERM)
- eigenvalue decomposition (EVD)
- explainability
Read from the server itself, by connecting to it and calling resources/list on 5 November 2026.
A listing does not declare its resources, so asking is the only way to know them, and this
is what the server actually offers rather than what its listing claims. Names only are
stored; connect the server for each resource's type and contents.