Search Results

TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning

1 code implementation27 Feb 2019

TensorFlow Eager is a multi-stage, Python-embedded domain-specific language for hardware-accelerated machine learning, suitable for both interactive research and production.

BIG-bench Machine Learning

Scikit-learn: Machine Learning in Python

3 code implementations2 Jan 2012

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems.

BIG-bench Machine Learning Clustering +3

Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms

1 code implementation SCIPY 2013 2013

Sequential model-based optimization (also known as Bayesian optimization) is one of the most efficient methods (per function evaluation) of function minimization.

Bayesian Optimization BIG-bench Machine Learning +2

Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning

2 code implementations21 Sep 2016

Imbalanced-learn is an open-source python toolbox aiming at providing a wide range of methods to cope with the problem of imbalanced dataset frequently encountered in machine learning and pattern recognition.

AutoML BIG-bench Machine Learning +1

River: machine learning for streaming data in Python

2 code implementations8 Dec 2020

It is the result from the merger of the two most popular packages for stream learning in Python: Creme and scikit-multiflow.

BIG-bench Machine Learning Continual Learning

CausalML: Python Package for Causal Machine Learning

2 code implementations25 Feb 2020

CausalML is a Python implementation of algorithms related to causal inference and machine learning.

BIG-bench Machine Learning Causal Inference

SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives

5 code implementations NeurIPS 2014

In this work we introduce a new optimisation method called SAGA in the spirit of SAG, SDCA, MISO and SVRG, a set of recently proposed incremental gradient algorithms with fast linear convergence rates.

Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence

2 code implementations12 Feb 2020

Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline.

BIG-bench Machine Learning

Foolbox: A Python toolbox to benchmark the robustness of machine learning models

6 code implementations13 Jul 2017

Foolbox is a new Python package to generate such adversarial perturbations and to quantify and compare the robustness of machine learning models.

Adversarial Attack BIG-bench Machine Learning

BindsNET: A machine learning-oriented spiking neural networks library in Python

1 code implementation4 Jun 2018

In this paper, we describe a new Python package for the simulation of spiking neural networks, specifically geared towards machine learning and reinforcement learning.

BIG-bench Machine Learning Neural Network simulation +3