You can Start Making a Difference in Every Field with Deep Learning

What is Deep Learning and How Does it Function?

Deep learning is a machine learning method that consists of a multi-layered structure that predicts the results provided by the data. Deep learning, machine learning; Machine learning is a sub-branch of artificial intelligence.

Artificial intelligence, which emerged in the early 1950s, started to take place in technology as systems that perform specific tasks and constantly renew themselves, similar to human intelligence. On the other hand, machine learning emerged in the early 1980s and entered our lives as a form of knowledge put forward by processing the dataset and making predictions. However, both forms of learning have been waiting behind dusty sides for many years without showing any improvement. Contrary to these two learning, a different form of learning has come to the fore. This form of knowledge, which emerged at the beginning of the 2000s, has started to attract significant attention in the market as “Deep Learning” and has begun to make a name for itself.

So why didn’t this Artificial Intelligence and Machine Learning make progress in those years?

  1. Lack of data,
  2. Financial inadequacy,
  3. False activation functions,
  4. The slow progress of computer development,

Over time, with the development of technology, insufficient computers in artificial intelligence operations became more robust, data sets grew, and new algorithms were developed with existing algorithms. Thus, developments in artificial intelligence and machine learning began to be observed. However, parallel to these learnings developments in the field of “Deep Learning” began to be experienced one after the other. One of the essential features in this learning area is that the more data input for the learning process, the more successful it is.

 Uses of Deep Learning

  1. In alarm systems,
  2. In driverless vehicles,
  3. In cyber threat analysis,
  4. In recommendation systems,
  5. In the health sector (such as cancer research),
  6. In face recognition and voice recognition systems,
red and orange fish lot

Apart from these areas, another area that benefits from deep learning is an intelligent fish farming area. So how does this field benefit from deep learning? For example, fresh and saltwater fish, aquarium fish, reducing mortality in an aquaculture environment, etc. Therefore, deep learning systems that will contribute to the developments in the subject seem to make a significant contribution to the sector in this field. At this point, if we need to take a look at the structures established in the field of intelligent fish farming, together with the deep learning systems that will form the infrastructure of the underwater imaging and reporting system for this area, the entire production cycle from the spawning period to the time when the production in the fish farming area is completed, including camera and sensor systems will be transferred to the system. In this way, deep learning systems, which will work in partnership with artificial intelligence systems that will combine the biological records obtained with the information of the fish species, will provide data analysis and image processing algorithms using various machine learning algorithms. In this way, a comprehensive report will be presented to the people involved in the production phase. Of course, in the preparation phase of this report, the areas that benefit from deep learning should not be overlooked. At this point, the systems to be used for information collection can be listed as follows.

  1. IoT
  2. Sensors
  3. Energy systems
  4. Display systems
  5. Artificial intelligence
  6. Communication systems

Deep learning continues to surprise us with innovations that will make a difference in many areas. While doing this, it continues to lead this progress in one field and different fields within the scope of a comprehensive framework. At this point, deep learning, which also uses its systems in the field of intelligent fish farming, informs everyone about technological developments. In addition, it mobilizes its systematic features that will provide ease of use for many areas by causing innovations that will show its presence in every field where technology is developed. At this point, deep learning systems, which pioneered the development of methods in smart fish farming, which has been mobilized, add a new dimension to smart fish farming by working in partnership with many systems. In this way, we see that deep learning is a pioneer in many sectors.

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