Average Ratings 0 Ratings
Average Ratings 2 Ratings
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.
Description
TensorFlow is a comprehensive open-source machine learning platform that covers the entire process from development to deployment. This platform boasts a rich and adaptable ecosystem featuring various tools, libraries, and community resources, empowering researchers to advance the field of machine learning while allowing developers to create and implement ML-powered applications with ease. With intuitive high-level APIs like Keras and support for eager execution, users can effortlessly build and refine ML models, facilitating quick iterations and simplifying debugging. The flexibility of TensorFlow allows for seamless training and deployment of models across various environments, whether in the cloud, on-premises, within browsers, or directly on devices, regardless of the programming language utilized. Its straightforward and versatile architecture supports the transformation of innovative ideas into practical code, enabling the development of cutting-edge models that can be published swiftly. Overall, TensorFlow provides a powerful framework that encourages experimentation and accelerates the machine learning process.
API Access
Has API
API Access
Has API
Integrations
Keras
Python
ZenML
ApertureDB
Axolotl
Cleanlab
Cyfuture Cloud
EasyODM
FlytBase
IBM Cloud
Integrations
Keras
Python
ZenML
ApertureDB
Axolotl
Cleanlab
Cyfuture Cloud
EasyODM
FlytBase
IBM Cloud
Pricing Details
$179 per user per month
Free Trial
Free Version
Pricing Details
Free
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
Comet
Founded
2017
Country
United States
Website
www.comet.com/site/products/llmops/
Vendor Details
Company Name
TensorFlow
Founded
2015
Country
United States
Website
www.tensorflow.org
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
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization