AI vs ML vs DL - Studyopedia

05 Oct AI vs ML vs DL

Posted at 11:36h in Deep Learning by Studyopedia Editorial Staff 0 Comments

We learned about Deep Learning in the previous lessons. Let us see the difference between Artificial Intelligence, Machine Learning, and Deep Learning.

	Artificial Intelligence (AI)	Machine Learning (ML)	Deep Learning (DL)
What?	Artificial Intelligence means creating smart machines to mimic human behavior	In Machine Learning, the computer is fed with data and information. This gives these systems the ability to learn and enhance from experiences.	Deep Learning uses neural networks to model and solve complex problems
Subset/ Superset	AI is a superset of both ML and DL	ML is a subset of AI.	DL is a subset of ML.
Easy or Complex	Easier rules to advanced algorithms	Uses algorithms like decision trees, SVM, etc.	Uses complex neural networks with many layers.
Data	Can work with structured data and predefined rules	Needs structured data for training	Needs large amounts of labeled data for effective training
Human
Intervention	Human Intervention is high, especially in rule-based systems	Human Intervention is moderate, requires feature extraction	Human Intervention is low, since it has automatic feature extraction
Hardware Requirements	Generally lower, depends on application	Moderate, can run on standard hardware	High, requires GPUs for training deep networks. Modern GPUs (Graphics Processing Units) are used for parallel computation.
Applications/ Uses	Robotics, game playing, etc.	Email filtering, healthcare, recommendation systems, etc.	Image and speech recognition, language processing, etc.
Efficiency	Varies based on complexity and design	Generally good with sufficient data	Often superior performance with large datasets
Learning Techniques	Rule-based learning, expert systems, etc.	Supervised, unsupervised, and reinforcement learning	Primarily supervised and unsupervised learning with deep networks