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Average Ratings 0 Ratings

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Description

Empowering businesses to engage in genuine data science quickly and effectively through a comprehensive machine learning platform is crucial. By minimizing the time spent managing tools and infrastructure, organizations can concentrate on developing machine learning applications that drive growth. Anaconda Enterprise alleviates the challenges associated with ML operations, grants access to open-source innovations, and lays the groundwork for robust data science and machine learning operations without confining users to specific models, templates, or workflows. Software developers and data scientists can seamlessly collaborate within AE to create, test, debug, and deploy models using their chosen programming languages and tools. Additionally, AE facilitates access to both notebooks and integrated development environments (IDEs), enhancing collaborative efficiency. Users can also select from a variety of example projects or utilize preconfigured projects tailored to their needs. Furthermore, AE automatically containerizes projects, ensuring they can be effortlessly transitioned between various environments as required. This flexibility ultimately empowers teams to innovate and adapt to changing business demands more readily.

Description

Manage and optimize models throughout the entire ML lifecycle. This includes experiment tracking, monitoring production models, and more. The platform was designed to meet the demands of large enterprise teams that deploy ML at scale. It supports any deployment strategy, whether it is private cloud, hybrid, or on-premise servers. Add two lines of code into your notebook or script to start tracking your experiments. It works with any machine-learning library and for any task. To understand differences in model performance, you can easily compare code, hyperparameters and metrics. Monitor your models from training to production. You can get alerts when something is wrong and debug your model to fix it. You can increase productivity, collaboration, visibility, and visibility among data scientists, data science groups, and even business stakeholders.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Apache Spark
Axolotl
Azure Data Science Virtual Machines
Clone Protocol
CogniSync
Dask
Flask
Google Cloud Platform
IBM Cloud
IBM watsonx.data
Jovian
Keras
Kixie PowerCall & SMS
Microsoft Azure
NVIDIA RAPIDS
New Relic
OpenSCAP
ZenML

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Apache Spark
Axolotl
Azure Data Science Virtual Machines
Clone Protocol
CogniSync
Dask
Flask
Google Cloud Platform
IBM Cloud
IBM watsonx.data
Jovian
Keras
Kixie PowerCall & SMS
Microsoft Azure
NVIDIA RAPIDS
New Relic
OpenSCAP
ZenML

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$179 per user per month
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

Anaconda

Country

United States

Website

www.anaconda.com/enterprise/

Vendor Details

Company Name

Comet

Founded

2017

Country

United States

Website

www.comet.com/site/products/llmops/

Product Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Machine Learning

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

Product Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Deep Learning

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

Machine Learning

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

Alternatives

Alternatives

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