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Description
DEP AIWorks is an innovative AI platform created by DEP, aimed at revolutionizing the engineering process from conception through development and optimization. This platform sits at the crossroads of engineering knowledge and state-of-the-art AI/ML technologies, empowering organizations to speed up product development, improve decision-making, and foster large-scale innovation.
By integrating smoothly with current engineering workflows, DEP AIWorks facilitates intelligent automation throughout design, simulation, and analysis tasks. It encompasses advanced features such as smart pre-processing, parametric modeling, predictive insights, and optimization, ultimately delivering enhanced efficiency, precision, and responsiveness in CAE-driven engineering.
Prioritizing scalability and practical applications, DEP AIWorks caters to a variety of industries including automotive, aerospace, and industrial equipment, among others. As a result, engineering teams benefit from reduced development timelines, heightened performance, and the ability to make informed, data-driven decisions with certainty. This platform not only enhances productivity but also paves the way for future technological advancements in engineering.
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
API Access
Has API
Screenshots View All
No images available
Integrations
GitHub
Python
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
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
Detroit Engineered Products
Founded
1998
Country
United States
Website
www.depusa.com
Vendor Details
Company Name
Axel ARONIO DE ROMBLAY
Founded
2017
Website
mlbox.readthedocs.io/en/latest/
Product Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Engineering
2D Drawing
3D Modeling
Chemical Engineering
Civil Engineering
Collaboration
Design Analysis
Design Export
Document Management
Electrical Engineering
Mechanical Engineering
Mechatronics
Presentation Tools
Structural Engineering
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization