Climin is a Python package for optimization, heavily biased to machine learning scenarios

Overview

climin

climin is a Python package for optimization, heavily biased to machine learning scenarios distributed under the BSD 3-clause license. It works on top of numpy and (partially) gnumpy.

The project was started in winter 2011 by Christian Osendorfer and Justin Bayer. Since then, Sarah Diot-Girard, Thomas Rueckstiess and Sebastian Urban have contributed. If you use climin in your (academic) work, please cite as (tech report is in preparation):

J. Bayer and C. Osendorfer and S. Diot-Girard and T. Rückstiess and Sebastian Urban. climin - A pythonic framework for gradient-based function optimization. TUM Tech Report. 2016. http://github.com/BRML/climin

Important links

Dependencies

The software is tested under Python 2.7 with numpy 1.10.4, scipy 0.17. The tests are run with nosetests.

Installation

Use git to clone the official repository; then run pip install --user -e . in the clone to intall in your local user space.

Testing

From the download directory run nosetests tests/.

Owner
Biomimetic Robotics and Machine Learning at Technische Universität München
Biomimetic Robotics and Machine Learning at Technische Universität München
List of Data Science Cheatsheets to rule the world

Data Science Cheatsheets List of Data Science Cheatsheets to rule the world. Table of Contents Business Science Business Science Problem Framework Dat

Favio André Vázquez 11.7k Dec 30, 2022
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

Microsoft 8.4k Dec 30, 2022
Adaptive: parallel active learning of mathematical functions

adaptive Adaptive: parallel active learning of mathematical functions. adaptive is an open-source Python library designed to make adaptive parallel fu

741 Dec 27, 2022
A simple application that calculates the probability distribution of a normal distribution

probability-density-function General info An application that calculates the probability density and cumulative distribution of a normal distribution

1 Oct 25, 2022
Simulate & classify transient absorption spectroscopy (TAS) spectral features for bulk semiconducting materials (Post-DFT)

PyTASER PyTASER is a Python (3.9+) library and set of command-line tools for classifying spectral features in bulk materials, post-DFT. The goal of th

Materials Design Group 4 Dec 27, 2022
ArviZ is a Python package for exploratory analysis of Bayesian models

ArviZ (pronounced "AR-vees") is a Python package for exploratory analysis of Bayesian models. Includes functions for posterior analysis, data storage, model checking, comparison and diagnostics

ArviZ 1.3k Jan 05, 2023
Machine Learning Model to predict the payment date of an invoice when it gets created in the system.

Payment-Date-Prediction Machine Learning Model to predict the payment date of an invoice when it gets created in the system.

15 Sep 09, 2022
Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Microsoft 366 Jan 03, 2023
A simple python program that draws a tree for incrementing values using the Collatz Conjecture.

Collatz Conjecture A simple python program that draws a tree for incrementing values using the Collatz Conjecture. Values which can be edited: Length

davidgasinski 1 Oct 28, 2021
Mixing up the Invariant Information clustering architecture, with self supervised concepts from SimCLR and MoCo approaches

Self Supervised clusterer Combined IIC, and Moco architectures, with some SimCLR notions, to get state of the art unsupervised clustering while retain

Bendidi Ihab 9 Feb 13, 2022
Azure MLOps (v2) solution accelerators.

Azure MLOps (v2) solution accelerator Welcome to the MLOps (v2) solution accelerator repository! This project is intended to serve as the starting poi

Microsoft Azure 233 Jan 01, 2023
A toolkit for making real world machine learning and data analysis applications in C++

dlib C++ library Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real worl

Davis E. King 11.6k Jan 02, 2023
A logistic regression model for health insurance purchasing prediction

Logistic_Regression_Model A logistic regression model for health insurance purchasing prediction This code is using these packages, so please make sur

ShawnWang 1 Nov 29, 2021
A GitHub action that suggests type annotations for Python using machine learning.

Typilus: Suggest Python Type Annotations A GitHub action that suggests type annotations for Python using machine learning. This action makes suggestio

40 Sep 18, 2022
PySpark + Scikit-learn = Sparkit-learn

Sparkit-learn PySpark + Scikit-learn = Sparkit-learn GitHub: https://github.com/lensacom/sparkit-learn About Sparkit-learn aims to provide scikit-lear

Lensa 1.1k Jan 04, 2023
This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch

This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment to test the algorithm

Martin Huber 59 Dec 09, 2022
Decision Weights in Prospect Theory

Decision Weights in Prospect Theory It's clear that humans are irrational, but how irrational are they? After some research into behavourial economics

Cameron Davidson-Pilon 32 Nov 08, 2021
Combines Bayesian analyses from many datasets.

PosteriorStacker Combines Bayesian analyses from many datasets. Introduction Method Tutorial Output plot and files Introduction Fitting a model to a d

Johannes Buchner 19 Feb 13, 2022
InfiniteBoost: building infinite ensembles with gradient descent

InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De

Alex Rogozhnikov 183 Jan 03, 2023