How Deep Learning Has Evolved the World of Technology?

In the past six years, deep learning has made huge strides in its capabilities. This is due to improvements in compute power and algorithmic advances. It is now widely used in a wide variety of fields, from automatic text generation to medical diagnostics. It has also become a popular tool for voice-command applications and even weather forecasting.

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Feature extraction

One of the fundamental aspects of deep learning is feature extraction. It helps computer programs learn to recognize objects and process data. This process relies on algorithms that automatically construct meaningful “features” from the input data. Traditionally, software engineers had to manually select relevant features for their algorithms. However, with the advent of artificial neural networks (ANNs), feature extraction can be automatic. For example, the first hidden layer of an ANN might learn the shapes and edges of an image. The next layer might learn the colors of the image, while the last hidden layer might learn complex shapes.