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ease
features
design
support

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Description

Apache PredictionIO® is a robust open-source machine learning server designed for developers and data scientists to build predictive engines for diverse machine learning applications. It empowers users to swiftly create and launch an engine as a web service in a production environment using easily customizable templates. Upon deployment, it can handle dynamic queries in real-time, allowing for systematic evaluation and tuning of various engine models, while also enabling the integration of data from multiple sources for extensive predictive analytics. By streamlining the machine learning modeling process with structured methodologies and established evaluation metrics, it supports numerous data processing libraries, including Spark MLLib and OpenNLP. Users can also implement their own machine learning algorithms and integrate them effortlessly into the engine. Additionally, it simplifies the management of data infrastructure, catering to a wide range of analytics needs. Apache PredictionIO® can be installed as a complete machine learning stack, which includes components such as Apache Spark, MLlib, HBase, and Akka HTTP, providing a comprehensive solution for predictive modeling. This versatile platform effectively enhances the ability to leverage machine learning across various industries and applications.

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

Screenshots View All

Integrations

Python
AWS Marketplace
Apache HBase
Apache Hadoop YARN
Apache Spark
Docker
Elasticsearch
GitHub
Java
MySQL
PHP
PostgreSQL
Ruby
Scala

Integrations

Python
AWS Marketplace
Apache HBase
Apache Hadoop YARN
Apache Spark
Docker
Elasticsearch
GitHub
Java
MySQL
PHP
PostgreSQL
Ruby
Scala

Pricing Details

Free
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

Apache

Country

United States

Website

predictionio.apache.org

Vendor Details

Company Name

Axel ARONIO DE ROMBLAY

Founded

2017

Website

mlbox.readthedocs.io/en/latest/

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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