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On the Link Between Optimization and Polynomials, Part 6. Optimization Nuggets: Stochastic Polyak Step-size, Part 2 Optimization Nuggets: Stochastic Polyak Step-size On the Convergence of the Unadjusted Langevin Algorithm The Russian Roulette: An Unbiased Estimator of the Limit Notes on the Frank-Wolfe Algorithm, Part III: backtracking line-search On the Link Between Optimization and Polynomials, Part 5 Optimization Nuggets: Implicit Bias of Gradient-based Methods Optimization Nuggets: Exponential Convergence of SGD On the Link Between Optimization and Polynomials, Part 4 On the Link Between Optimization and Polynomials, Part 3 On the Link Between Optimization and Polynomials, Part 2 On the Link Between Polynomials and Optimization, Part 1 How to Evaluate the Logistic Loss and not NaN trying Notes on the Frank-Wolfe Algorithm, Part II: A Primal-dual Analysis Three Operator Splitting Notes on the Frank-Wolfe Algorithm, Part I Optimization inequalities cheatsheet A fully asynchronous variant of the SAGA algorithm Hyperparameter optimization with approximate gradient Lightning v0.1 scikit-learn-contrib, an umbrella for scikit-learn related projects. SAGA algorithm in the lightning library On the consistency of ordinal regression methods Holdout cross-validation generator PyData Paris - April 2015 Data-driven hemodynamic response function estimation Plot memory usage as a function of time Surrogate Loss Functions in Machine Learning Different ways to get memory consumption or lessons learned from ``memory_profiler`` Numerical optimizers for Logistic Regression Logistic Ordinal Regression Isotonic Regression Householder matrices Loss Functions for Ordinal regression Memory plots with memory_profiler Singular Value Decomposition in SciPy Learning to rank with scikit-learn: the pairwise transform line-by-line memory usage of a Python program Low rank approximation qr_multiply function in scipy.linalg scikit-learn 0.9 Reworked example gallery for scikit-learn scikit-learn’s EuroScipy 2011 coding sprint -- day two scikit-learn EuroScipy 2011 coding sprint -- day one Ridge regression path LLE comes in different flavours Manifold learning in scikit-learn Handwritten digits and Locally Linear Embedding Low-level routines for Support Vector Machines new get_blas_funcs in scipy.linalg Locally linear embedding and sparse eigensolvers scikits.learn is now part of pythonxy Least squares with equality constrain A profiler for Python extensions scikit-learn coding sprint in Paris py3k in scikit-learn Computing the vector norm Smells like hacker spirit New examples in scikits.learn 0.6 Weighted samples for SVMs Coming soon ... memory efficient bindigs for libsvm solve triangular matrices using scipy.linalg LARS algorithm Second scikits.learn coding sprint Support for sparse matrices in scikits.learn Flags to debug python C extensions. July in Paris Support Vector machines with custom kernels using scikits.learn Howto link against system-wide BLAS library using numpy.distutils scikits.learn 0.2 release Plot the maximum margin hyperplane with scikits.learn Fast bindings for LibSVM in scikits.learn scikits.learn coding sprint in Paris Scikit-learn 0.1 scikit-learn project on sourceforge After holidays Winter in Paris is not funny Last days in Granada Learning, Machine Learning Moving to Paris! Summer of Code is over Speed improvements for ask() (sympy.queries.ask) Logic module (sympy.logic): improving speed Refine module Query module - finally in trunk django, change language settings dynamically can we merge now, pleeease ? Refine module, proof of concept Preparing a new release Efficient DPLL algorithm Queries and performance Reading CNF files Logic module merged The boolean satisfiability problem Initial implementation of the query system Assumption system and automatic theorem proving. Should I be learning LISP ? Homenaje a Antonio Vega en La Percha

IPython/Jupyter notebook gallery

Fabian Pedregosa · 2015-04-21 · via Keep the gradient flowing

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