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What is Deep Learning?

Deep Learning is a type of machine learning that enables a machine to learn using neural networks (inspired by the structure and function of the human brain). Before continuing with this post it would be beneficial to read over our post on Neural Networks. Many data scientists would use deep learning as a way to get outputs from a large amount of data.

How does deep learning work?

 

An artificial brain depicting an explanation of what is deep learning.

Deep learning is a type of machine learning that is best equipped to traverse through a large amount of Neural Networks. There are many examples of deep learning; Siri, Alexa and Cortana would be using AI to process a question or request from their user. This AI would be interacting with a huge neural network to get the results required by the user.

One good example of how deep learning works is that it would process the neural network of data by very rapidly running true or false tests. Over time as the deep learning process continues a machine or computer would train itself on what results need to be displayed based on what they are asked. The probability or accuracy of answers would also improve over time.

One example of a result of deep learning would be Google Translate’s ability to detect a language being inputted or Google Search’s ability to predict the rest of a search term being inputted into the search engine.  Over time we have seen the predictions improve compared to when they were first released to the market.

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