What is the difference between machine learning (ML), deep learning (DL) and artificial intelligence (AI)?

Machine Learning, Deep Learning, and Artificial Intelligence are concepts used in the fields of computer science and artificial intelligence. While closely related, there are some key differences between them. Here are the main differences:

Artificial Intelligence (AI)

Artificial Intelligence is the broader concept referring to machines' ability to perform tasks related to human intelligence. The goal of AI is for machines to think, learn, and solve problems, similar to the human brain. AI is a comprehensive term that can include machine learning and deep learning.

Machine Learning (ML)

Machine Learning is a specific subset of artificial intelligence that applies learning techniques based on data. Machine learning allows machines to learn from data and interpret it without explicit programming. Machine learning algorithms are used to discover patterns and relationships in data, enabling decisions or predictions to be made based on them.

Deep Learning (DL)

Deep Learning is a subset of machine learning that draws inspiration from the functioning of neural networks in the human brain. Deep Learning uses neural networks, which are complex structures, to learn and model higher-level representations of data. The application of Deep Learning involves multi-layered networks that are capable of automatically extracting features and learning from data without the need for explicitly defined functions or features.

In summary, Artificial Intelligence is a broader concept that encompasses machine learning and deep learning. Machine Learning is a method for implementing artificial intelligence that focuses on machines learning and adapting from data. Deep Learning is a specialized form of machine learning that uses neural networks to learn and model higher-level representations.