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One of the most common questions people ask is which IDE/environment/ tool to use while working on your data science/AI projects. As you would expect, there is no dearth of options available – from language-specific IDEs like R Studio, PyCharm to editors like Sublime Text or Atom – the choice can be intimidating for a beginner.

If there is one tool that every data scientist should use or must be comfortable with, it is Jupyter Notebooks. Jupyter Notebooks are powerful, versatile, shareable and provide the ability to perform data visualization in the same environment. Jupyter Notebooks allow to create and share documents, from codes to full-blown reports and most important is that its Open-Source. so sharing official Jupyter Notebook Documentation
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One of the most common questions people ask is which IDE/environment/ tool to use while working on your data science/AI projects. As you would expect, there is no dearth of options available – from language-specific IDEs like R Studio, PyCharm to editors like Sublime Text or Atom – the choice can be intimidating for a beginner.

If there is one tool that every data scientist should use or must be comfortable with, it is Jupyter Notebooks. Jupyter Notebooks are powerful, versatile, shareable and provide the ability to perform data visualization in the same environment. Jupyter Notebooks allow to create and share documents, from codes to full-blown reports and most important is that its Open-Source. so sharing official Jupyter Notebook Documentation

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One of the most common questions people ask is which IDE/environment/ tool to use while working on your data science/AI projects. As you would expect

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