Deep learning is based on the concept of What is the neural networks, which are a type of technology that attempts to simulate the functioning and behavior of the human brain.
Thus, deep learning big data allows the system to understand a high volume of information and offer immediate responses and results with this data.
Deep learning is an evolutionary branch of machine learning, so to speak. This is because while machine learning is linear and facilitates a machine’s ability to learn, it also offers it the ability to develop and evolve as it learns and is exposed to complex data (big data), deep learning offers much more complex analysis and understanding.
When to use machine learning?
Machine learning can be used in different contexts and situations. We have separated three everyday examples so that you can understand it better.
Recommendation systems : Streaming services like Amazon Prime Video use machine learning to analyze and identify their gambling database customers’ patterns. This way, they are able to recommend movies and series based on their preferences.
Fraud detector: Banks and credit card companies use machine learning to detect and combat fraud. Here, the system can identify suspicious behavior and block unwanted actions.
Disease treatment: Machine learning is quite effective in preventing and treating diseases. It is used in image diagnosis. To do this, the system compares images and analyzes changes that indicate possible disorders.
How is machine learning used in chatbot? What is the
Machine learning is also color psychology: how to use this technique to sell more? successfully used in customer service . In this area, it is carried out through the chatbot , which can learn by interacting with the user.
In a simpler way, deep learning “trains” the computer and allows it to autonomously learn to recognize and identify patterns b2b phone list in various layers of the processing structure and thus be able to offer answers so that it can perform several tasks at the same time.
