Previously there was only artificial intelligence (AI), though now we have so many others intelligence process such as machine learning (ML), deep learning (DL), supervised learning, Natural Language Processing (NLP) etc.
So what makes machine learning and deep learning different from artificial intelligence?
Artificial intelligence (AI) is a subject which encompasses all the areas which are making machines smarter.
Artificial intelligence is the parent category of all other computer learning subjects such as machine learning and deep learning.
Coming back to the initial question regarding the difference between AI, ML and DL, below is some explanations.
Artificial intelligence (AI)
AI refers to making a computer to mimic human behaviour in some way. It is quite old and goes back to the 1950s. It is a subset of data science.
Machine Learning (ML)
Machine learning is a subset of AI and data science, and its history goes back to 1960s. It covers the techniques which enable computers to learn from the data and produce AI applications. It is subdivided into:
(1) Supervised Learning. It is tasked-driven learning which predicts the next value. The learning process is using labelled data, direct feedback and predicts outcome/future.
(2) Unsupervised Learning. It is a data-driven learning process to identify the cluster. It learns without labels and feedback to find hidden structure/pattern.
(3) Reinforcement learning It is decision process and rewards system and learns through a series of actions. It learns from mistakes.
The below image shows the machine learning and its applications.
Deep Learning (DL)
Deep learning is the subset of machine learning, and its history originates around 1970s, though it gets more traction around 2010. It helps computers to solve more complex issues by using artificial neural networks.
AI is not just about ML and DP, but there are more subsets and subject areas.
A simplified version of artificial intelligence is below.
A more details mind map of artificial intelligence is here.