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Formulate and solve common regression and classification models such as ridge, lasso, logistic, and SVM as convex optimization problems.
Distinct from Machine Learning Optimization: Distinct from Machine Learning Optimization: focuses on formulating ML models as convex optimization problems, not general training efficiency.
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CVXPY is a Python-embedded domain-specific language for modeling and solving convex optimization problems using natural mathematical syntax. It is built on a disciplined convex programming framework that automatically enforces convexity rules, ensuring that problems formulated by the user are valid for convex solvers. The project also functions as a multi-solver optimization interface, abstracting away backend details and dispatching problems to specialized solvers like ECOS, SCS, and Gurobi without manual configuration. Beyond standard convex optimization, CVXPY extends its reach to geometri
Fits regression and classification models like ridge, lasso, logistic, and SVM as convex optimization problems.