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Deep Learning

The Unseen Intelligence: How Deep Learning AI is Quietly Impacting Our Everyday Lives

Deep learning is a subfield of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data. While a neural network with a single layer can still make approximate predictions, additional hidden layers can help to optimize and refine for accuracy.

Deep learning drives many artificial intelligence (AI) applications and services that automate decision-making, reasoning, and problem-solving. It has led to significant advancements in various fields, including computer vision, natural language processing, speech recognition, and self-driving cars.

Deep learning models can be trained to recognize patterns, classify objects, detect anomalies, predict outcomes, and even generate new data points based on what they’ve learned. This is done using labeled (supervised) or unlabeled (unsupervised) training data, as well as a combination of both (semi-supervised).

Some popular deep learning frameworks include TensorFlow, Keras, PyTorch, and Caffe. These frameworks provide tools and libraries for designing, training, and deploying neural networks efficiently.

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