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ease
features
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support

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Description

MLBox is an advanced Python library designed for Automated Machine Learning. This library offers a variety of features, including rapid data reading, efficient distributed preprocessing, comprehensive data cleaning, robust feature selection, and effective leak detection. It excels in hyper-parameter optimization within high-dimensional spaces and includes cutting-edge predictive models for both classification and regression tasks, such as Deep Learning, Stacking, and LightGBM, along with model interpretation for predictions. The core MLBox package is divided into three sub-packages: preprocessing, optimization, and prediction. Each sub-package serves a specific purpose: the preprocessing module focuses on data reading and preparation, the optimization module tests and fine-tunes various learners, and the prediction module handles target predictions on test datasets, ensuring a streamlined workflow for machine learning practitioners. Overall, MLBox simplifies the machine learning process, making it accessible and efficient for users.

Description

STOCHOS is an advanced probabilistic AI solution designed specifically for engineering and research and development applications. It harnesses existing simulation, testing, and measurement data to swiftly predict new variants while providing uncertainty assessments for each prediction, allowing engineers to discern when to trust the results or opt for traditional solvers. Utilizing the DIM-GP framework, STOCHOS is effective even with limited datasets, ranging from just a few dozen to a few hundred samples, and can handle various data types such as scalars, signals, 2D and 3D fields, meshes, geometries, and images. Its capabilities include surrogate modeling, uncertainty quantification, Bayesian and multi-objective optimization, as well as multi-fidelity modeling and sensitivity analysis, along with generative geometry techniques. STOCHOS Flow, a user-friendly visual workbench, enables the creation of workflows without the need for coding, allowing teams to deploy them as web applications. The software operates on local hardware and can be installed offline, ensuring accessibility and privacy. Founded in 2018 in Grafing bei München, PI Probaligence is part of the CADFEM Group and has established itself as a technology partner with Ansys, promoting innovative solutions in engineering. Furthermore, its ability to integrate seamlessly into existing processes enhances productivity and drives efficiency in engineering teams.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

No images available

Integrations

GitHub
Python

Integrations

GitHub
Python

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Quote on request
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Axel ARONIO DE ROMBLAY

Founded

2017

Website

mlbox.readthedocs.io/en/latest/

Vendor Details

Company Name

PI Probaligence GmbH

Founded

2018

Country

Germany

Website

probaligence.com

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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