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features
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support

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Description

ClearML is an open-source MLOps platform that enables data scientists, ML engineers, and DevOps to easily create, orchestrate and automate ML processes at scale. Our frictionless and unified end-to-end MLOps Suite allows users and customers to concentrate on developing ML code and automating their workflows. ClearML is used to develop a highly reproducible process for end-to-end AI models lifecycles by more than 1,300 enterprises, from product feature discovery to model deployment and production monitoring. You can use all of our modules to create a complete ecosystem, or you can plug in your existing tools and start using them. ClearML is trusted worldwide by more than 150,000 Data Scientists, Data Engineers and ML Engineers at Fortune 500 companies, enterprises and innovative start-ups.

Description

Segmind simplifies access to extensive computing resources, making it ideal for executing demanding tasks like deep learning training and various intricate processing jobs. It offers environments that require no setup within minutes, allowing for easy collaboration among team members. Additionally, Segmind's MLOps platform supports comprehensive management of deep learning projects, featuring built-in data storage and tools for tracking experiments. Recognizing that machine learning engineers often lack expertise in cloud infrastructure, Segmind takes on the complexities of cloud management, enabling teams to concentrate on their strengths and enhance model development efficiency. As training machine learning and deep learning models can be time-consuming and costly, Segmind allows for effortless scaling of computational power while potentially cutting costs by up to 70% through managed spot instances. Furthermore, today's ML managers often struggle to maintain an overview of ongoing ML development activities and associated expenses, highlighting the need for robust management solutions in the field. By addressing these challenges, Segmind empowers teams to achieve their goals more effectively.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Hyperbolic No 
Kubernetes Yes 

Integrations

Hyperbolic Yes 
Kubernetes No 

Pricing Details

$15
Per seat, add - ons, support.
Custom pricing - Enterprise
Free Trial Yes 
Free Version Yes 

Pricing Details

$5
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
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

ClearML

Founded

2016

Country

Israel

Website

clear.ml/

Vendor Details

Company Name

Segmind

Founded

2020

Country

India

Website

Segmind.com

Product Features

Deep Learning

Convolutional Neural Networks Yes 
Document Classification Yes 
Image Segmentation Yes 
ML Algorithm Library Yes 
Model Training Yes 
Neural Network Modeling Yes 
Self-Learning Yes 
Visualization Yes 

DevOps

Approval Workflow No 
Dashboard Yes 
KPIs No 
Policy Management Yes 
Portfolio Management No 
Prioritization Yes 
Release Management Yes 
Timeline Management No 
Troubleshooting Reports No 

Machine Learning

Deep Learning Yes 
ML Algorithm Library No 
Model Training Yes 
Natural Language Processing (NLP) Yes 
Predictive Modeling Yes 
Statistical / Mathematical Tools Yes 
Templates Yes 
Visualization Yes 

Virtual Machine

Backup Management Yes 
Graphical User Interface Yes 
Remote Control Yes 
VDI Yes 
Virtual Machine Encryption Yes 
Virtual Machine Migration No 
Virtual Machine Monitoring Yes 
Virtual Server Yes 

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

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 

Alternatives