Deep Learning is termed ‘Deep’ due to multiple additional ‘layers’ added to learn from the data. Whenever a deep learning model is learning, it updates the weights across an optimisation function. Essentially, a Layer is a transitional row of ‘Neurons’. A deep learning method sequentially learns categories via its hidden layer architecture. Firstly, it establishes low-level categories like letters and then moves to slightly higher-level classes such as words. Finally, it moves to the higher-level categories like sentences.