even more interesting is the autonomous
Every node in these deep layer learns the set of features automatically. It then aims to reconstruct the input and tries to do so by minimizing the guesswork with each passing node. It doesn't need specific data and in fact is so smart that draws co-relations from the feature set to get optimal results. They are capable of learning gigantic data sets with numerous parameters, and form structures from unlabelled or unstructured data. Now, let's take a look the key differences: Differences: The future with Machine Learning and Deep Learning: Moving further, let's take a look at the use cases of both Machine Learning and Deep Learning. However, one should note that Machine Learning use cases are available while Deep Learning are still in the developing stage. While Machine Learning plays a huge role in Artificial Intelligence, it is the possibilities introduced by Deep Learning that is changing the world as we know it. These technologies will see a future in many industries,...