Machine learning nes training so that it knows how to work and act in each situation. In deep learning! we provide the system with only basic information so that the neural network can begin to be built. From there! it can evolve automatically. All you ne to do is provide the data so that it can take advantage of the information on its own! which will make its own performance increasingly better.
Both deep learning and machine learning have the ability to learn! but deep learning performs much more complex and in-depth analyses. In addition! it has the ability to recognize and perform multiple tasks simultaneously! bas on the data it has collect.
We explain that deep learning
Can be us in practically all sectors and for the most diverse applications. In fact! it is already being us and is part of the daily lives of people and companies! often without them realizing it is happening.
It is possible to use! for example! for artificial vision! precisely accurate mobile phone number list what allows for the facial recognition we mention. In addition to recognizing characters! images and objects! bringing the possibility of application in quality control in industry 4.0.
We can also apply deep learning to perform prictive analyses in order to make prictions with greater accuracy! efficiently directing decisions and investments within companies.
It is applicable in customer service
Since chatbots can be programm with this type of artificial intelligence. It is present in virtual assistants! which respond to voice commands.
In healthcare! deep learning is us to obtain diagnoses! for example. But there are other applications! such as:
robotics;
suggestion of entertainment content;
personalization of news and advertising;
music composition;
recognition of customer twitter and shares with them behavior patterns;
early identification taiwan lists of signs of failures in systems or processes;
identification of What are the applications fraud patterns.