Many Industry sectors are looking towards Deep Learning – a form of AI technology. Both of these new ways of working have increasing relevance as we make further technological advances and develop a greater understanding of data and the insights it brings.
In order to understand how Deep Learning can assist let us take a look below at its definition.
What Is Deep Learning?
Focusing on the deep and multi-layered neural network, the primary concern of Deep Learning is to train this layer to reproduce specific functions. When manipulated appropriately, these intense brain layers have shown to reproduce functions such as the Universal Turing Machine. However, the difficulty faced by technology experts is how to configure them to create results.
Although not a completely revolutionary proposition, with a large enough set of training data, we are able to reconfigure or in simpler language, to train the neural networks to complete, decipher and decode tasks that we previously have not been able to.
Let’s take a look below to find out if we have the ability to access the training data required.
Do We Have the Power to Access Deep Learning Data?
Training Deep Neural Networks is extremely expensive as large data sets are required in order to train them adequately.
We have only recently acquired the computational capability required in order to access the data, along with the ability to access the data required for Deep Learning to showcase its potential.
The use of NVIDIA graphics cards revolutionized the process and Deep learning is now almost predominantly trained on GPU’s, which is a specialized electronic circuit which is designed to provide computations all at the same time, rather than one after the other with a CPU.
Now we understand that we have only recently obtained the potential to access the data required for deep learning, let’s look at what we have learned from previous technologies from past decades.
What We’ve Learned About Neural Networks
Since the ’80s and ’90s, we have learned that computers have now become fast enough to cope with the demands of manipulating neural network training. We know the capacity in terms of larger data sets with the advent of imaging and video data, and through other improvements in technology.
How Does Deep Learning Work?
A special type of neural network in which an artificial neuron is connected to a window over a previous network layer is called a convolution neural network and it’s by this method that the most common form of deep learning is applied.
To understand how deep learning works, with regards to a visual task, the Neurons in the first convolution layer may only be able to see a few pixels of an image. The convolution layer comprises of several maps which each explore and search for a different feature. In turn, each Neuron searches for that particular feature in a separate position.
We hope this article has given a brief overview and introduction to this cutting-edge fascinating form of data analysis.
Disclaimer: The author of this text, Robin Trehan, has an Undergraduate degree in economics, Masters in international business and finance and MBA in electronic business. Trehan is Senior VP at Deltec International www.deltecbank.com. The views, thoughts, and opinions expressed in this text are solely the views of the author, and not necessarily reflecting the views of Deltec International Group, its subsidiaries and/or employees.