Deep learning is a branch of machine learning based on the artificial neural networks which automatically optimize their learned rules/ patterns when there’s a wrong prediction.
Following are some of the Deep learning definitions from the sources.
Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks.
https://machinelearningmastery.com/what-is-deep-learning/
Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised.
https://en.wikipedia.org/wiki/Deep_learning
Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: learn by example. Deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost.
https://www.mathworks.com/discovery/deep-learning.html
The Concept – Deep Learning
- Deep learning model consists of more than 2 layers of artificial neural networks with a number of nodes
- Each node represents a weighted number which contributes to the overall calculation/interpretation of the output from the given input
- Each node is started with a random weighted number which is incremented in each forward pass with a small ratio known as Learning Rate
- The wights of each node are adjusted if the predicted value of the target class doesn’t match the actual value of the class.
- The process is repeated until either the defined number of epochs/ iterations are completed or the model fully learn the hidden parameters to predict the target class with maximum success rate
Types of Deep Neural Networks
- Feed Forward Neural Networks (FFNNs)
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- Long Short Term Memory Network (LSTM)
- Gated Recurrent Neural Network (GRNN)
- Self Organizing Maps (SOMs)
- Boltzmann Machines
- Auto Encoders
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