Machine learning and deep learning rely on datasets to work. Without the proper dataset, sometimes even processed AI processes do not work. In the case of deep learning, one requires cleaned, labelled and categorized datasets. This is essential for the neural network to be as accurate as possible. The entire concept of deep learning works on layers of data to make sense. All the decision making, forecasting and classification depends on data. So, in a way, data is the most crucial part of deep learning. The framework and modelling can be done with several libraries. Even in data science, to use machine learning, the most important part is Data cleaning. Exploratory data analysis and data cleaning are important parts on which results depend.
Let us have a look at some of the publicly available datasets for deep learning purposes: