What is Deep Learning and why everyone is talking about it?

Deep learning (DL) is a subtype of machine learning, which in turn is a subject of artificial intelligence. It is a machine learning technique that teaches computers to do what is natural for humans: learn by example.

How does it work?

In DL, a computer model learns to perform classification tasks directly from images, text, or sound. DL models can achieve state-of-the-art accuracy, sometimes exceeding human-level performance. The models are trained using a large set of labeled data and neural network architectures containing many layers.

DL has received a lot of attention lately, and for good reason. What are the significant reasons for using it

Huge amount of data

ML works well with small data, but when you supply a huge amount of data to the model, algorithms cannot solve this problem. This is why DL is becoming more popular than ML, because the amount of data is growing exponentially, and this type of training can easily solve this problem regardless of the size of the data.

Real problems

DL can easily solve complex real-world problems. Deep Learning is a key technology at the heart of self-driving cars, allowing them to recognize signs and distinguish pedestrians from streetlights. This is the key to voice control in consumer devices like phones, tablets, TVs.


In machine learning, to train a model, you must manually enter all the functions associated with your problem. In deep learning, you only need to supply objects or data, you don’t need to supply functions manually. DL only generates high-order functions that help you predict the result yourself!

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