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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

Parameter serves as an extensive monitoring solution designed to assist critical facilities in identifying, analyzing, and responding to environmental, leak, and equipment health challenges before they lead to failures. By consolidating data from RLE leak detection systems, battery monitoring (Cellwatch), and environmental observations, it creates a cohesive system that delivers real-time insights to building management systems (BMS) via standard protocols such as SNMP, BACnet, and Modbus. The platform is adaptable, enabling monitoring capabilities that range from individual racks to large-scale operations, while ensuring accurate detection of fluid leaks with location mapping, ongoing surveillance of temperature, humidity, airflow, CO2, and power conditions, as well as comprehensive battery health analysis for UPS and backup systems. Parameter’s offerings include instant alerts and actionable insights through web interfaces that can be accessed from any browser or device, facilitating prompt responses and proactive maintenance to enhance operational uptime. This powerful tool not only improves efficiency but also fosters a proactive approach to facility management, ultimately ensuring a more resilient infrastructure.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

GitHub
Modbus RTU
Python
SNMP .Net Component

Integrations

GitHub
Modbus RTU
Python
SNMP .Net Component

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

Parameter

Founded

2024

Country

United States

Website

parameter-tech.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

Facility Management

Asset Management
Commercial Properties
Equipment Management
Facility Scheduling
Incident Management
Inspection Management
Inventory Control
Maintenance Tracking
Preventive Maintenance
Residential Properties
Room Scheduling
Schools
Space Planning
Vendor Management
Visitor Management
Work Order Management

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