Deep Learning

Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural network.

Where is Deep learning used?

Deep learning applications are used in industries from automated driving to medical devices. Automated Driving: Automotive researchers are using deep learning to automatically detect objects such as stop signs and traffic lights. In addition, deep learning is used to detect pedestrians, which helps decrease accidents.

What is deep learning? Why is this a growing trend in machine learning?

The “deep” in “deep learning” refers to the number of layers through which the data is transformed. Deep learning has a large number of layers as compared to classical neural networks. More layers capture more statistical invariances. See the full article for more details.

Why is it called deep learning?

Deep Learning is all about Neural Networks. Each neuron receives the signal, processes the signal, and passes it on to the other neurons. This is how the information is passed on in our brain. Similarly, Neural Networks contains 3 layers i.e. input layer, hidden layer, output layer.

What is deep learning and its applications?

Deep Learning has a wide range of application ranging from product development to producing a new drug, from medical diagnosis to producing fake news and music. Deep Learning is being widely used in industries to solve large number of problems like computer vision, natural language processing and pattern recognition.

Who invented deep learning?

The history of Deep Learning can be traced back to 1943, when Walter Pitts and Warren McCulloch created a computer model based on the neural networks of the human brain. They used a combination of algorithms and mathematics they called “threshold logic” to mimic the thought process.