7 Nov 2022

Deep Learning vs Machine Learning


‘Machine Learning’ and ‘Deep Learning’ have become buzz terms, with the rapid development of more sophisticated AI. But what is the difference?

Venn diagram depiction of AI, Machine Learning and Deep Learning

Both Machine Learning (ML) and Deep Learning (DL) are forms of Artificial Intelligence. AI models are used so that computers can make intelligent decisions, 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 are different in how much work is required of us humans to train these models, before they can make good decisions. Often, Machine Learning requires human intervention before a particular 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 the human provides the model with a set of training data, with the ‘answers’ hidden from the model until it makes its predictions. This training data is called ‘labelled data’. The model can then compare its predictions with the answers and adjust itself appropriately, using a feedback loop; when the answer is correct, the algorithm rewards the model, when it’s incorrect, the algorithm punishes the model. This reward/punishment loop is called reinforcement learning. When the model is rewarded for a particular action, it essentially strengthens the decision pathway leading to that action. 

What is Deep Learning?

Deep Learning is a subset of Machine Learning and uses layered structures, which mimic the human brain. These are called Artificial Neural Networks (ANNs) and 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’.

This series of videos provide an excellent visual demonstration of ANNs >> 

In summary:

  • Machine Learning is a kind of AI which uses algorithms to analyse data and learn patterns from it.
  • Deep Learning is a subset of Machine Learning which uses layered structures called Artificial Neural Networks (ANNs) to copy the way that humans learn. Therefore they are more independent.

Want to learn more about where an interest in Machine Learning could take you? Read this article about how a passion for ML and data science could bring you a role working in MI6>> 


Article by Britt Dewing, Stemettes Intern

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