When we think of Artificial Intelligence, it becomes almost overwhelming to wrap our brains around complex terms like Machine Learning, Deep Learning, and Natural Language Processing (NLP). After all, these new-age disciplines are much more advanced and intricate than anything we’ve ever seen. This is primarily why people tend to use AI terminologies synonymously, sparking a debate of sorts between different concepts of Data Science.
One such trending debate is that of Deep Learning vs. NLP. While Deep Learning and NLP fall under the broad umbrella of Artificial Intelligence, the difference between Deep Learning and NLP is pretty stark!
In this post, we’ll take a detailed look into the Deep Learning vs. NLP debate, understand their importance in the AI domain, see how they associate with one another, and learn about the differences between Deep Learning and NLP.
So, without further ado, let’s get straight into it!
Deep Learning is a branch of Machine Learning that leverages artificial neural networks (ANNs)to simulate the human brain’s functioning. An artificial neural network is made of an interconnected web of thousands or millions of neurons stacked in multiple layers, hence the name Deep Learning.
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