What is Deep Learning?

Deep Learning is a subset of Machine Learning (ML) based on the concept of artificial neural networks. It can be used to solve a variety of tasks using both structured and unstructured data.

The inspiration for Deep Learning emerged from biological systems. That's why they're vaguely designed to mimic the brain.

The recent surge in the popularity of Deep Learning is because we have access to vast amounts of data and computing resources.

What is Deep Learning used for?

Deep Learning models perform exceedingly well on a wide variety of tasks, especially those related to the fields of computer vision and language.

Google’s latest Deep Learning architecture called BERT achieves State Of The Art performances in various language tasks such as paraphrasing text or text generation. These models even outperform humans in tasks such as answering questions from given passages.

In computer vision, deep learning can be used for a variety of tasks, from detecting Pneumonia from chest X-rays to generating images of people that do not exist.

How can you get started with Deep Learning?

There are several Deep Learning frameworks that make the process of getting  hands-on with deep learning quick and seamless.

The most popular tools for Deep Learning are TensorFlow, PyTorch and Keras. Once you have a clear idea of the basic mathematical theory behind Deep Learning models, you can start implementing models fairly quickly using these tools.

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