Identify and categorize recurring errors with solutions to prevent repeated mistakes. Utilizes pattern recognition to enhance learning and streamline decision-making processes.
MIT
70,466 tools. Last updated 2026-02-08 01:03
- Transform arrays for machine learning preprocessing and data normalization using L2 normalization, standardization, min-max scaling, or log transformation.MIT
- Analyze numerical data to calculate descriptive statistics, identify quartiles, and detect outliers using Polars-based methods.MIT
- Perform Time Value of Money calculations to solve for present value, future value, payments, interest rates, IRR, or NPV using known financial variables.MIT
- Decompose matrices using eigenvalues/vectors, SVD, QR, Cholesky, or LU factorisation for linear algebra analysis and computational workflows.MIT
- Perform matrix decompositions including eigenvalues/vectors, SVD, QR, Cholesky, and LU factorizations to analyze linear algebra problems.MIT
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