This feature is located in the Learning tab, which is then followed by being under the Documentation tab. With that being said, if you are more senior level, then feel free to go on to the next sections where you will find out more about more complex use cases in data science. ![]() This first feature is for beginning data scientists who are just starting to learn how to code, or for data scientists who may want to freshen up and sharpen their Python skills. With that in mind, keep on reading if you would like to learn five things about the Anaconda Navigator platform. Some of these tools might be particularly useful for data scientists who are just beginning in their career, while some of these tools will be more beneficial for the more seasoned data scientists, as you will see below. I will be discussing these features that coincide with the more popular features like the Jupyter Notebook. However, they are still important and may be something that you have not looked into yet. The latter two features are ones that we may miss, because they are not directly related to writing your own immediate code and working on your machine learning algorithm in the main notebook application. As you navigate out of the home page or the home dashboard, you will see that there are the Environments, Learning, and Community sections. ![]() It is usually at these three applications where we tend to stop looking into this platform for other tools. Data scientists often use Anaconda Navigator, which houses popular and useful applications like JupyterLab, Jupyter Notebook, and RStudio.
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