The Difference Between Machine Learning and Deep Learning

Deep learning and machine learning are not the same thing. Although both fall under the study of artificial intelligence, they have distinct meanings.

What's the difference?

• Machine learning is the branch of artificial intelligence that focuses on the study of algorithms enabling machines to learn autonomously. It encompasses various techniques, cases, and approaches.

  Note: Generally, machine learning algorithms analyze a dataset to construct a predictive model capable of autonomously classifying objects and accurately responding to queries within a specific knowledge domain. They may rely on supervised, unsupervised, or reinforcement learning techniques.
  

• Deep learning (in-depth or advanced study) is a specialized subset of machine learning that utilizes artificial neural networks (neural networks) with two or more layers (hidden layers) to process information in a nonlinear manner.
  

This explanation should already be simple, clear, and comprehensive.

However, to grasp the concepts of deep learning (DL), machine learning (ML), and artificial intelligence (AI), it's helpful to keep this logical framework in mind.

Artificial Intelligence (AI) encompasses machine learning (ML) and much more (expert systems, signal theory, operational research, logic, ontologies, etc.).

In turn, machine learning (ML) includes deep learning (DL) as well as other automatic learning techniques.

This should now be much clearer.