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Average Ratings 0 Ratings
Description
Maintain your usual routine while working within Jupyter Notebooks or any Python setting. Just invoke modelbi.deploy to launch your model, allowing Modelbit to manage it — along with all associated dependencies — in a production environment. Machine learning models deployed via Modelbit can be accessed directly from your data warehouse with the same simplicity as invoking a SQL function. Additionally, they can be accessed as a REST endpoint directly from your application. Modelbit is integrated with your git repository, whether it's GitHub, GitLab, or a custom solution. It supports code review processes, CI/CD pipelines, pull requests, and merge requests, enabling you to incorporate your entire git workflow into your Python machine learning models. This platform offers seamless integration with tools like Hex, DeepNote, Noteable, and others, allowing you to transition your model directly from your preferred cloud notebook into a production setting. If you find managing VPC configurations and IAM roles cumbersome, you can effortlessly redeploy your SageMaker models to Modelbit. Experience immediate advantages from Modelbit's platform utilizing the models you have already developed, and streamline your machine learning deployment process like never before.
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
No
API Access
Has API
No
Integrations
Amazon Redshift
Yes
GitHub
Yes
Jupyter Notebook
Yes
PyTorch
Yes
Snowflake
Yes
TensorFlow
Yes
Amazon Athena
No
Amazon EMR
No
Amazon S3
No
Apache Spark
No
Integrations
Amazon Redshift
Yes
GitHub
Yes
Jupyter Notebook
Yes
PyTorch
Yes
Snowflake
Yes
TensorFlow
Yes
Amazon Athena
Yes
Amazon EMR
Yes
Amazon S3
Yes
Apache Spark
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
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
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
Modelbit
Founded
2022
Country
United States
Website
www.modelbit.com
Vendor Details
Company Name
Zepl
Founded
2016
Country
United States
Website
www.zepl.com/product/
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
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