Answer :
Deep Learning (DL) is a type of Artificial Intelligence (AI) that uses a set of algorithms to simulate the functioning of the human brain.
It is a form of machine learning that is based on the concept of neural networks. DL uses a set of algorithms to process large volumes of data and identify patterns in the data. DL can be used to identify patterns and relationships in data that are not easily visible to the human eye.
DL works by using a series of layers of neurons, each of which is connected to the next layer by a set of weights and biases. During the training process, these weights and biases are adjusted so that the output of the neural network is adjusted to match the desired output. This is done by using an optimization algorithm such as gradient descent. At each step, the weights and biases are adjusted until the output of the neural network matches the desired output.
Once the DL model has been trained, it can be used to make predictions from new data. It does this by taking inputs and passing them through the layers of neurons to generate an output. This output is then compared to the desired output and an error is calculated. This error is then used to adjust the weights and biases in order to minimize the error. This process of adjusting the weights and biases is repeated until the error is minimized and the model can make accurate predictions from new data.
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What is Deep Learning (DL)?
