Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
No
API Access
Has API
No
Screenshots View All
No images available
Integrations
GitHub
No
Python
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
Quote on request
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
No
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
No
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
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
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No