Deep learning is part of the greater machine learning concept. It is about learning algorithms that provide function and structure of the brain known as artificial neural networks.
Getting started with deep learning can leave you feeling confused. But with a deeper dive, it is possible to learn more about deep learning and what it can achieve.
Large Neural Networks
Deep learning technologies run into places that you may not have realized. For instance, a large array of Google services make use of deep learning. It is about using brain simulations to make learning algorithms not only better, but easier to use.
It is also about making advances in AI and machine learning that can have a plethora of benefits. The belief is that we now have enough data and fast enough computers to train those large neural networks.
Scalable Applications for Deep Learning
The real question is what deep learning can help to achieve. Where deep learning really excels is where inputs and even some outputs are analog. Basically, they are documents of text data, files of audio data, or images of pixel data.
That can lead to object and facial recognition software, for instance. Utilizing multilayer perceptron feedforward neural networks means scaling model size and data.
Computer Vision
A real-life application of deep learning is computer vision. This is what powers drones, self-driving cars, and a number of other biometric processes. It does this by comprehending the visual environment and then deciphering the context.
Utilizing deep learning, computer vision can identify and then classify images. It does so through labeled, predefined categories.
NLP
Natural language processing takes algorithms and analyzes and interprets human language inputs in either verbal or textual formats. This includes sentiment analysis, text classification, speech recognition, translation, and so much more.
We see real-world applications of this in popular smart assistants like Alexa, Cortana, and Siri. There are also chatbots and adaptive email filters, just the tip of the iceberg for what natural language processing can potentially have to offer.