{"id":1012,"date":"2022-04-23T02:52:35","date_gmt":"2022-04-23T02:52:35","guid":{"rendered":"https:\/\/uplatz.com\/blog\/?p=1012"},"modified":"2023-03-26T08:26:03","modified_gmt":"2023-03-26T08:26:03","slug":"what-is-deep-learning-how-deep-learning-works-algorithms-used-in-deep-learning","status":"publish","type":"post","link":"https:\/\/uplatz.com\/blog\/what-is-deep-learning-how-deep-learning-works-algorithms-used-in-deep-learning\/","title":{"rendered":"What is Deep Learning, How Deep Learning Works, Algorithms used in Deep Learning"},"content":{"rendered":"

\"\"<\/span>What is Deep learning?<\/span><\/h2>\n

Deep learning is a subfield of machine learning and artificial intelligence which copy the way the human brain gains certain knowledge. It is a powerful set of techniques for learning in neural networks. The meaning of the ‘Deep’ in deep learning is referring to the depth of the layers in a neural network. <\/span>A deep learning model is created with the help of a neural network that consists of artificial neurons. <\/span><\/p>\n

A neural network is divided into three major layers input layer( it is the first layer of the neural network where we get input), hidden layer (it is the second layer of our neural network which help us to us accurate input on how much-hidden layer in our model that much accurate output we get) and output layer (This is our third or last layer where we get output).<\/span><\/p>\n

How Deep learning works<\/span><\/h2>\n

A deep neural network is also referred to as a deep learning model because it uses neural network architectures for its research. A normal neural network model only consists of three layers Input layer, the hidden layer, and the output layer but a deep network can consist of as many as 150 hidden layers and the main thing is how much-hidden layers in our model that much accurate output we get. <\/span><\/p>\n

We used deep learning algorithms to train our model (detection algorithms, such as radial-bias functions, multilayer perceptrons, etc, to eliminate the need to manually extract features). Visible layers are the input and output layers of a deep network. The input layer is where the deep learning model is get the data for processing, and the output layer is where the final prediction or classification gets.<\/span><\/p>\n

After we gave input from the input layer, we used deep learning algorithms to train our model (algorithms such as conventional neural networks, radial-bias function, multilayer perceptron, etc, and the algorithms also eliminated the manual feature extraction). and then our model gives us an accurate output in this way deep learning is work. We also use backpropagation algorithms to calculate errors in predictions. (Backpropagation algorithms are like gradient descent, Boltzmann learning, Hebbian learning, etc)<\/span><\/p>\n

Some Algorithms used in Deep Learning<\/span><\/h2>\n