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support

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Description

Amazon SageMaker equips users with an extensive suite of tools and libraries essential for developing machine learning models, emphasizing an iterative approach to experimenting with various algorithms and assessing their performance to identify the optimal solution for specific needs. Within SageMaker, you can select from a diverse range of algorithms, including more than 15 that are specifically designed and enhanced for the platform, as well as access over 150 pre-existing models from well-known model repositories with just a few clicks. Additionally, SageMaker includes a wide array of model-building resources, such as Amazon SageMaker Studio Notebooks and RStudio, which allow you to execute machine learning models on a smaller scale to evaluate outcomes and generate performance reports, facilitating the creation of high-quality prototypes. The integration of Amazon SageMaker Studio Notebooks accelerates the model development process and fosters collaboration among team members. These notebooks offer one-click access to Jupyter environments, enabling you to begin working almost immediately, and they also feature functionality for easy sharing of your work with others. Furthermore, the platform's overall design encourages continuous improvement and innovation in machine learning projects.

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.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker Yes 
Amazon Web Services (AWS) Yes 
Docker Yes 
GitHub Yes 
Google Cloud AutoML Yes 
Jupyter Notebook Yes 
Kubernetes No 
MXNet Yes 
PyTorch Yes 
Python Yes 
R Yes 
R Markdown Yes 
TensorFlow Yes 

Integrations

Amazon SageMaker No 
Amazon Web Services (AWS) No 
Docker No 
GitHub No 
Google Cloud AutoML No 
Jupyter Notebook No 
Kubernetes Yes 
MXNet No 
PyTorch No 
Python No 
R No 
R Markdown No 
TensorFlow No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

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

Deployment

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

Deployment

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

Customer Support

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

Customer Support

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

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/sagemaker/build/

Vendor Details

Company Name

ClearML

Founded

2016

Country

Israel

Website

clear.ml/

Product Features

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 

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 

Alternatives