Heavy learning is growing in both popularity plus revenue. In this article, we will shed light on the different milestones that have led to the deep learning field we know today. Some of these events include the introduction of the initial neural network model in 1943 and the first use of this technology, in 1970.
We will certainly then address more recent achievements, starting with Google’s Neural Machine Translation and moving on to the lesser known innovations such as the Pix2Code – an application that is used to generate a specific layout code to defined screenshots with 77% accuracy.
Towards the end of the article, we will briefly touch on automated learning-to-learn algorithms and democratized deep learning (embedded deep studying in toolkits).
The Past – An Overview associated with Significant Events
1943 – The Initial Mathematical Model of a Neural Network
For deep learning to develop there needed to be an established understanding of the neural networks in the human brain.
A logician and a neuroscientist – Walter Pitts plus Warren McCulloch respectively, created the first neural network mathematical model. Their work, ‘A logical Calculus of Ideas Immanent in Nervous Activity’ was published, and it put forth a combination of algorithms plus mathematics that were aimed at mimicking…
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