Why do we need Deep Learning?

• In the present scenarios, most of the problems in artificial intelligence like Image Segmentation, Image Classification and many more are solving using Deep Leaning models. So the question is if we have many machine learning algorithms and what is Deep Learning and Why do we need it?

Source:Edureka

• By the following picture we can see that there are some limitations of Machine Learning. 
• The major distinguishing factor of deep learning compared to more traditional methods is the ability of the performance of the classifiers to large scaled with increased in quantities of data.

Source: becominghuman.ai

• Older machine learning algorithms typically plateau in performance after it reaches a threshold of training data. Deep learning is one-of-a-kind algorithm whose performance continues to improve as more the data fed, the more the classifier is trained on resulting in outperforming more than the traditional models/ algorithm.
• The execution time is comparatively more for deep learning , as it needed to be trained with lots of data. The major drawback of this ability to scale with additional training data is a need for trusted data that can be used to train the model.  
• Machine Learning Vs Deep Learning

So, what happens in Deep Learning?

The software learns, in a very realistic sense, to recognize patterns in digital representations of images, sounds, censor data and other data. We are pre-training data, in order to classify or predict and build a train/training set and test set(we know the result). And on prediction obtaining a optimal point such that our prediction gives a satisfying result.