Exploring Jupyter Notebooks

While working on a project relating to deep learning, you must deal with a huge amount of variables of various types and arrays of various dimensions. Also, since the data contained in them is massive and keeps changing after nearly every step, we need a tool that helps us to observe the output produced by each step so that we can proceed accordingly. A Jupyter Notebook is one such tool. Jupyter Notebooks are known for their simplicity, and their wide support of features and platforms are currently the standard tool for developing deep-learning solutions. The reasons for their popularity can be understood by considering the fact that several of the top tech giants offer their own version of the tool, such as Google Colaboratory and Microsoft Azure Notebooks. Moreover, the popular code-hosting website GitHub has been providing a native rendering of Jupyter Notebook since 2016.