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What are open source projects?
Open Source means anybody is free to use, study, modify, and distribute your project for any purpose.
I am personally interested in open source projects because it is free, and it is also a good way to build your project portfolio.
I have compiled a list of Jupyter notebooks open source for your day-to-day data science projects
Jovian
Jovian is a platform for sharing and collaborating on Jupyter notebooks and data science projects. Jovian-py is an open-source Python package for uploading your data science code, Jupyter notebooks, ML models, hyperparameters, metrics etc. to your Jovian account.
NAAS
Naas is an open source that allows access to live business insights from data which provides a real competitive advantage.
Naas low-code formulas, notebooks are more readable, more accessible, and interconnected to support faster business decision-making.
Naas is an open-source platform that allows data professionals (business analysts, scientists and engineers) to create data engines combining automation, analytics and AI from the comfort of their Jupyter notebooks.
Observable HQ
Observable hq reveal insights from your data, collaborate with others, and use visualizations to present those insights to others.
Observable hq uses JavaScript framework for visualization such as D3
You can share and collaborate with others, within a team, and across the platform. You can share what you create and learn from others. Observable helps break down walls between people and tools (e.g. developers and data scientists can work together).
Elyra
Elyra is an AI Pipelines visual editor
Elyra provides a Pipeline Visual Editor for building AI pipelines from notebooks, Python scripts and R scripts, simplifying the conversion of multiple notebooks or scripts files into batch jobs or workflows.
Happy Learning with jupyter notebook open source projects.