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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
Artificial intelligence (AI) and computer vision play a crucial role in enhancing manufacturing processes by training systems to ensure product quality, guiding robots for autonomous movement and safety protocols, and equipping cameras to monitor and analyze retail traffic, identify various car types and colors, recognize food items in a refrigerator, or generate 3D models from video footage. Additionally, these advanced technologies utilize algorithms to forecast sales, uncover relationships between different metrics and publications, and facilitate business growth, as well as categorize customers to tailor personalized offers, interpret and visualize data, and extract key information from text and video content. Techniques such as data mining, regression analysis, classification, correlation, and cluster analysis, along with decision trees and prediction models, are employed alongside neural networks to optimize outcomes. Furthermore, text analysis encompasses classification, comprehension, summarization, auto-tagging, named-entity recognition, and sentiment analysis while also enabling comparison for text similarity, dialog systems, and question-answering frameworks. Image and video processing is further enhanced through detection, segmentation, recognition, recovery, and the generation of new visual content, showcasing the vast potential of AI in various domains. This multifaceted application of AI not only streamlines operations but also opens up new avenues for innovation and efficiency in multiple industries.
API Access
Has API
API Access
Has API
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
Axel ARONIO DE ROMBLAY
Founded
2017
Website
mlbox.readthedocs.io/en/latest/
Vendor Details
Company Name
PureMind
Founded
2017
Country
Russian Federation
Website
puremind.tech/
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
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)