Outstanding Data Science Tools



What you get with MLJAR

MLJAR with it's all tools is the right place if you're looking for:

Solid open-source machine

Discover frameworks developed by and for the community, and take the first step towards contributing to open-source projects.

Sharing your notebooks

Without rewriting the Python notebook... make your analysis accessible to even non-technical.

Automate your work

Save your time by using our tools, e.g., automate the process of building a machine learning pipeline or schedule your notebook.

Looking for experts

Utilize our expertise – facing an issue? We can offer you our time.

Machine Learning explained and deployed

Next-generation AutoML with fairness metrics and extensive explanation in the form of automatically generated documentation.

Seeking for innovations

We developed some custom projects using LLM for data analysis.

Data Science Tools

Automated Machine Learning

The most advanced AutoML with the simplest User Interface

A state-of-the-art tool designed for Data Science professionals. Our platform provides advanced automated machine learning capabilities, enabling effective model creation and data analysis process optimization.

Automatic report with documentation

Each model built using mljar AutoML is described in detailed documentation with charts.

The only AutoML with Fairness

Use the fairness metric if you want to avoid discrimination by the machine learning models you create.

The easiest & fastest way to build ML models

Creating models with AutoML in such a brief timeframe and with such precision beyond human reach.

Automate all stages of creating a machine learning pipeline, and explore how our features work:

Features preprocessing

Features selection

Algorithm selection

Golden features

Models ensembling

ML explainability

A few steps to achieve your goals!

Define your goals

Clearly outline your analytics goals while specifying how machine learning algorithms can contribute to achieving those objectives.

Provide a good data set & implement MLJAR

Prepare your data for machine learning. Valuable data set is the key to achieve profitable results. Then install mljar-supervised, and let the magic begin!

Deploy models and visualize

Deploy your results or use Mercury. Use the wide visualize libraries to make your work attractive for non-technical users.

Work is done! Coffee time :)

AutoML steps








Data Science Tools


Turn your Python Notebook into a Web App with the open-source Mercury framework. Share your results with non-technical users.

Mercury allows you to add interactive widgets in Python notebooks, so you can share notebooks as web applications. Forget about rewriting notebooks to web frameworks just to share your results. Mercury offers a set of widgets with simple re-execution of cells.

Share multiple notebooks

You can share as many notebooks as you want and set the authentication.

Don't worry about layout

Widgets are in the sidebar and outputs will appear in the same order as in the notebook.

No callbacks!

Mercury automatically re-executes cells below updated widget. You don't need to write callbacks to handle widget update.

Mercury- the easiest way to turn your notebook into web app, dashboard or report!

Start with Python Notebook

Python Notebook is a great tool to connect Markdown, Python code and outputs into meaningful documents.

Make it interactive

Add widgets to you Python Notebook and make it interactive.

Run as Web App

Start Mercury Server and serve your notebook as Web App.

Deploy with Mercury Cloud

Deployment as easy as file upload. Set custom domain and use secure connection.



Data scientists and researchers worldwide extensively utilize our products, and below, you'll find several testimonials showcasing their experiences.

Hugo Santos Silva

Lead Data Engineer

"Mercury seems to be very interesting. Just had a try today and was able to fire up a GUI within 10 minutes that would have taken me at least 2h using Panel. Really nice thing."

Knut Jägersberg

Data Scientist

"MLJAR AutoML, because of its user-centric design."

Katarzyna-Anna Bensch

Data Analyst

"Mercury provides useful widgets so my apps are interactive, but with desired limits set since users can not edit the code. The layout provided by Mercury framework makes anyone feel comfortable because of its clean and flawless look. Knowing this framework made my collaborations much more efficient. "

Joshua Jäger

Data Scientist

"I just, wanted to thank you for this amazing AutoML package and tool! I am currently putting together a package that builds on MLJAR and tweaks it specifically for use with data typically available in the field of clinical psychology."

Vivek Sinha

Chief Operating Officer

"I just looked at the mljar-supervised package. It's really thorough and much more in depth than other AutoML solutions I have used in the past. The compete param is also pretty awesome! Love it. Congratulations on the great work! Not surprised it is getting rapid adoption."


Software Developer

"After changing to use Mercury framework, I get to simplify my code a lot without having to deal with the widget listeners and layout"

Start revolutionize your data journey!

Take the next step towards innovation – try our tools or explore collaboration opportunities now.