Warm welcome to the new tutorial on “Difference between Machine learning and Artificial Intelligence”. Machine Learning and Artificial intelligence are two hot topics, and often seem to be used interchangeably. But these terms aren’t same thing.
“The ability of machines to work and think, like the human brain, is called Artificial Intelligence.”
Artificial intelligence can be interpreted as adding human intelligence in machine. Artificial intelligence is not a system but a discipline that focuses on making machine smart enough to tackle the problem like human brain does.
Machine Learning is the subset of AI. That is, all machine learning counts as AI, but not all AI counts as machine learning. Machine learning refers to the system that can learn by themselves. Machine learning is the study of computer algorithms that comprises of algorithms and statistical models which allow computer programs to automatically improve through experience.
John McCarthy, widely recognized as one of the godfathers of AI, defined it as “the science and engineering of making intelligent machines.”
Machine Learning is the science of getting computers to act by feeding them data and letting them learn a few tricks on their own without being explicitly programmed.
Difference between Machine learning and Artificial Intelligence
- Artificial intelligence focuses on Success whereas Machine Learning focuses on Accuracy
- AI is not a system, but it can be implemented on system to make system intelligent. ML is a system that can extract knowledge from datasets
- AI is used in decision making whereas ML is used in learning from experience
- AI mimics human whereas ML develops self-learning algorithm
- AI leads to wisdom or intelligence whereas ML leads to knowledge or experience
- Machine Learning is one of the way to achieve Artificial Intelligence.
“Machine learning is the tendency of machines to learn from data analysis and achieve Artificial Intelligence.”