Deep Learning is a specialized subset of Machine Learning

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While Machine Learning is a subset of Artificial Intelligence (AI), Deep Learning layers algorithms to create a neural network , which is an artificial replica of the structure and function of the brain.


This allows AI systems to continuously learn as they go and improve the quality and accuracy of their results. It also allows these systems to learn from unstructured data, such as photos, videos, and audio files. How does Deep Learning work? Deep Learning algorithms do not map inputs directly to outputs.


Instead, they rely on multiple layers of greece whatsapp number data processing units. Each layer passes its output to the next layer, which processes it and passes it on to the next layer. The multiple layers are why it is called “Deep Learning.


” When creating Deep Learning algorithms, developers and engineers configure the number of layers and the type of function that connects the output of each layer to the input of the next layer. They then train the model by feeding it many annotated examples.


For example: You feed a Deep Learning algorithm thousands of images and labels that correspond to the context of each image. The algorithm runs those examples through its multilayered neural network and adjusts the weights of the variables in each layer of the neural network so that it can detect common patterns that identify images with similar labels.