Machine Learning and Deep Learning are now popular, thanks to the rapid development of sophisticated AI. But what is the difference?
Both Machine Learning (ML) and Deep Learning (DL) are forms of Artificial Intelligence. AI models are used so computers can make intelligent decisions. More specifically, by learning from their mistakes without specific human instruction. Machine Learning and Deep Learning approach this problem in different ways.
What is Machine Learning?
ML and DL differ in how much work is required of us humans to train these models, before they can make good decisions. Often, ML requires human intervention before a model can be trained (called Supervised Machine Learning). The human has to extract the data to begin with, and if the model makes an inaccurate prediction, the human has to correct it.
In practice, this means that humans provide models with training data, but hide the ‘answers’ from the model until it makes its predictions. This training data is known as ‘labelled data’. The model then compares its predictions with the answers and adjusts itself appropriately. By using a feedback loop, when the answer is correct, the algorithm rewards the model. Conversely, when it’s incorrect, the algorithm punishes the model – known as reinforcement learning. When the model gets its reward for an action, it strengthens the decision pathway leading to that action.
What is Deep Learning?
DL is a subset of ML and uses layered structures, which mimic the human brain, known as Artificial Neural Networks (ANNs). These ANNs also consist of several layers of ‘nodes’. In the final layer, these nodes represent the outcomes of the model’s decision. For example, an ANN learning to recognise a pedestrian would have two outcome nodes in the final layer: ‘pedestrian’ and ‘not a pedestrian’.
- ML is a kind of AI which uses algorithms to analyse data and learn patterns from it.
- DL is a subset of ML using layered structures called Artificial Neural Networks to copy the way that humans learn; making them more independent.
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Article by Britt Dewing, Stemettes Intern