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What is marimo?

Introducing a cutting-edge reactive notebook tailored for Python, enabling users to perform repeatable experiments, execute scripts effortlessly, launch applications, and manage versions via git. 🚀 All-in-one solution: it effectively replaces tools like Jupyter, Streamlit, Jupytext, ipywidgets, and Papermill, among others. ⚡️ Adaptive: upon executing a cell, Marimo instantly processes all related cells or marks them as outdated. 🖐️ Interactive: effortlessly link sliders, tables, and graphs to your Python code without requiring callbacks. 🔬 Consistent: it eliminates hidden states, ensures deterministic execution, and incorporates built-in package management for reliability. 🏃 Versatile: can be run as a standard Python script, enabling adjustments through CLI arguments. 🛜 User-friendly: has the capability to morph into an interactive web application or presentation and operates seamlessly in the browser via WASM. 🛢️ Data-focused: proficiently queries dataframes and databases using SQL, while allowing easy filtering and searching through dataframes. 🐍 git-friendly: saves notebooks as .py files, simplifying version control processes. ⌨️ Modern editing: equipped with features like GitHub Copilot, AI assistants, vim keybindings, a variable explorer, and numerous other enhancements to optimize your workflow. With these advanced features, this notebook transforms your Python programming experience, fostering a more productive and collaborative coding atmosphere, making it easier to share insights and results with others.

What is Modelbit?

Continue to follow your regular practices while using Jupyter Notebooks or any Python environment. Simply call modelbi.deploy to initiate your model, enabling Modelbit to handle it alongside all related dependencies in a production setting. Machine learning models deployed through Modelbit can be easily accessed from your data warehouse, just like calling a SQL function. Furthermore, these models are available as a REST endpoint directly from your application, providing additional flexibility. Modelbit seamlessly integrates with your git repository, whether it be GitHub, GitLab, or a bespoke solution. It accommodates code review processes, CI/CD pipelines, pull requests, and merge requests, allowing you to weave your complete git workflow into your Python machine learning models. This platform also boasts smooth integration with tools such as Hex, DeepNote, Noteable, and more, making it simple to migrate your model straight from your favorite cloud notebook into a live environment. If you struggle with VPC configurations and IAM roles, you can quickly redeploy your SageMaker models to Modelbit without hassle. By leveraging the models you have already created, you can benefit from Modelbit's platform and enhance your machine learning deployment process significantly. In essence, Modelbit not only simplifies deployment but also optimizes your entire workflow for greater efficiency and productivity.

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Integrations Supported

Python

Integrations Supported

Amazon Redshift
Databricks
Deepnote
GitHub
GitLab
Google Colab
Jupyter Notebook
PyTorch
Snowflake
TensorFlow

API Availability

API Availability

Pricing Information

$0
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
Linux

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

marimo

Date Founded

2022

Company Location

United States

Company Website

marimo.io

Company Facts

Organization Name

Modelbit

Date Founded

2022

Company Location

United States

Company Website

www.modelbit.com

Categories and Features

Categories and Features

AI/ML Model Training

Not specified

Machine Learning

Not specified

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