Average Ratings 0 Ratings
Average Ratings 0 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
Coordinate, explore, and oversee all projects within your data science team efficiently. With Zepl's advanced search functionality, you can easily find and repurpose both models and code. The enterprise collaboration platform provided by Zepl allows you to query data from various sources like Snowflake, Athena, or Redshift while developing your models using Python. Enhance your data interaction with pivoting and dynamic forms that feature visualization tools such as heatmaps, radar, and Sankey charts. Each time you execute your notebook, Zepl generates a new container, ensuring a consistent environment for your model runs. Collaborate with teammates in a shared workspace in real time, or leave feedback on notebooks for asynchronous communication. Utilize precise access controls to manage how your work is shared, granting others read, edit, and execute permissions to facilitate teamwork and distribution. All notebooks benefit from automatic saving and version control, allowing you to easily name, oversee, and revert to previous versions through a user-friendly interface, along with smooth exporting capabilities to Github. Additionally, the platform supports integration with external tools, further streamlining your workflow and enhancing productivity.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Apache Spark
Yes
Keras
Yes
Plotly Dash
Yes
PyTorch
Yes
Python
Yes
TensorFlow
Yes
Amazon Athena
No
Amazon EMR
No
Amazon Redshift
No
Apache Zeppelin
No
Integrations
Apache Spark
Yes
Keras
Yes
Plotly Dash
Yes
PyTorch
Yes
Python
Yes
TensorFlow
Yes
Amazon Athena
Yes
Amazon EMR
Yes
Amazon Redshift
Yes
Apache Zeppelin
Yes
Pricing Details
$179 per user per month
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
Yes
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
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Comet
Founded
2017
Country
United States
Website
www.comet.com
Vendor Details
Company Name
Zepl
Founded
2016
Country
United States
Website
www.zepl.com/product/
Product Features
Data Science
Access Control
No
Advanced Modeling
No
Audit Logs
No
Data Discovery
No
Data Ingestion
No
Data Preparation
No
Data Visualization
No
Model Deployment
No
Reports
No
Deep Learning
Convolutional Neural Networks
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
Yes
Model Training
Yes
Neural Network Modeling
No
Self-Learning
No
Visualization
Yes
Machine Learning
Deep Learning
Yes
ML Algorithm Library
Yes
Model Training
Yes
Natural Language Processing (NLP)
Yes
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
Yes
Product Features
Data Science
Access Control
No
Advanced Modeling
No
Audit Logs
No
Data Discovery
No
Data Ingestion
No
Data Preparation
No
Data Visualization
No
Model Deployment
No
Reports
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
Predictive Analytics
AI / Machine Learning
No
Benchmarking
No
Data Blending
No
Data Mining
No
Demand Forecasting
No
For Education
No
For Healthcare
No
Modeling & Simulation
No
Sentiment Analysis
No