Deep Learning

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Introduction

Deep learning is an artificial intelligence function that makes patterns in the processing of the functioning of the human brain in data making and for use in decision making. Deep learning is a subset of machine learning in Artificial Intelligence (AI) that consists of networks that are capable of learning unheard of from unaided or unabeled data. It is also known as deep neural learning or deep neural networks.

How deep learning works

Deep learning has evolved hands-on with the digital age, which has exploded data from all forms and from every region of the world. This data, known as big data, is drawn from sources such as social media, Internet search engines, e-commerce platforms, and online cinema. This large amount of data is readily available and can be shared through fintech applications such as cloud computing.However, the data, which normally is unstructured, is so vast that it could take decades for humans to comprehend it and extract relevant information. Companies realize the incredible potential that can result from unraveling this wealth of information and are increasingly adapting to AI systems for automated support.

How Deep Learning Works

Another Example

It succeeds because it requires a large amount of label data. You can take an example from a driverless car. This advanced futuristic car needs more than a million images and also videos so that the car can distinguish and separate them all. This requires a great deal of computing power. The high-performance GPU has a parallel architecture that is efficient for this machine. If you combine it with clod or cluster computing, it will increase the development teams which can reduce the training time for the machine by hours, weeks or fixed time. Some methods are usually referring to the hidden layers inside the neural network. Basically, traditional networks have 2 or 3 hidden layers but deep and modern networks have more than 150 hidden layers. It now requires neural networks with labeled data without the need for manual help. This machine is distinguished from machine learning. The difference is that machine learning begins by manually extracting images as related features. Meanwhile, this machine can extract images automatically.

Deep Learning Example 2