Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
A premier solution for modeling, forecasting, and enhancing processes through multivariate statistical analysis and engaging visual representations. Accelerate product development, elevate quality, and refine processes by simplifying the analysis of extensive data sets more efficiently than previously possible. Achieve quicker and more precise solutions to practical challenges by examining diverse data types to enhance product creation, quality assurance, and manufacturing operations. Utilize advanced multivariate statistical analysis techniques, specifically designed for spectroscopy and chemometrics, to gain insights. Import material, sensor, process, and spectral data in various formats, complemented by easy-to-use features for plotting, preprocessing, and modeling spectral information. Ensure superior product classification to maintain consistent quality across offerings. Enhance productivity and simplify every stage of the analytical process with streamlined project-based workflows. Additionally, utilize compliance features such as digital signatures, password protection, and audit trails to adhere to regulations including 21 CFR Part 11 and EU Annex 11, ensuring your processes meet industry standards. This comprehensive tool empowers organizations to make informed decisions, fostering innovation and operational excellence throughout.
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.
API Access
Has API
No
API Access
Has API
No
Integrations
GitHub
No
Python
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
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
No
Linux
No
Chromebook
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
Customer Support
Business Hours
Yes
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
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Aspen Technology
Founded
1981
Country
United States
Website
www.aspentech.com/en/products/msc/aspen-unscrambler
Vendor Details
Company Name
Axel ARONIO DE ROMBLAY
Founded
2017
Website
mlbox.readthedocs.io/en/latest/
Product Features
Statistical Analysis
Analytics
Yes
Association Discovery
Yes
Compliance Tracking
Yes
File Management
No
File Storage
Yes
Forecasting
Yes
Multivariate Analysis
Yes
Regression Analysis
Yes
Statistical Process Control
Yes
Statistical Simulation
Yes
Survival Analysis
No
Time Series
No
Visualization
Yes
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