Definition of Deep Learning

What does is it mean and how is it used

What is Deep Learning? 

Deep Learning (sometimes known as deep structured learning or hierarchical learning) is part of Machine Learning. It’s focused on algorithms inspired by the structure and function of the brain called artificial neural networks. The heart of deep learning is using today’s superfast computers and masses of data to actually train large neural networks to act like a brain, which can learn over time.

Why use Deep Learning?

If you are interested in AI or Machine Learning, Deep Learning is a vital part of this. The idea of having a super brain of networks is obviously a contentious, highly complex and nuanced subject but whatever way you look at it, Deep Learning has the potential to radically transform how you use your data and infrastructure to do every aspect of business.

Latest Deep Learning Insights

Predictions 2019: Data Analytics trends to watch

Which technology trends will be game changing for your business in 2019? Read our predictions, in which we look at everything from how Python is tightening its grip in the world of machine learning, the rise of data-centricity, to new ways to merge BI and Data Science.

Read more on 2019’s tech trends >

Predictive Analytics: Anticipating who will click, buy or go elsewhere

It is time to start with data-driven decision making, selling the right products to the right clients, matching resoures better and recognizing trends quicker. Derive value from your data with Predicting Analytics.

Read more on Predictive Analytics >

Driving the rise of Artificial Intelligence and Machine Learning with data

AI and ML are disrupting a number of areas, including point of entry, automated backend processes, and knowledge management. A mix of IT and business decision makers were surveyed in their use of data analytics in order to fully understand the variances in perception and actions between these two pivotal decision-maker groups.

Read more on AI and ML >

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