What is AI and Machine Learning?
Generally we think Artificial intelligence and machine learning is the same thing but in reality it’s not. So in this blog we are going to see in brief what is AI and machine learning.
Artificial intelligence is the field of computer science, which makes computer systems a kind of intelligence. It consists of two words “Artificial” and “intelligence”, which means “a human-made thinking power”.
Therefore, we can say: “Artificial intelligence is a technology through which we can create intelligent systems that can simulate human intelligence.”
The artificial intelligence system does not need to be pre-programmed, but uses algorithms that can be used with its own intelligence. AI has been used in many places, such as Mobile Gaming, speech recognition, also in chess games, etc.
There are 3 types of artificial intelligence, namely weak AI,strong AI and artificial superintelligence.
Machine learning is about extracting knowledge from data. It can be defined as “Machine learning is a subfield of artificial intelligence that enables machines to learn from past data or experience without direct programming”. Machine learning allows a computer system to make predictions or take some decisions using historical data without being directly programmed. Machine learning uses a massive amount of structured and semi-structured data so that a machine learning model can generate accurate results or give predictions based on that data.
Machine learning works on algorithm which learn by it’s own using historical data. It works only for specific domains such as if we are creating a machine learning model to detect pictures of Lions, it will only give result for Lion images, but if we provide a new data like Tiger image then it will become unresponsive. Machine learning has been used in various places, such as Image recognition, online recommendation systems, Google search algorithms, Self driving cars, email spam filters, Facebook automatic friend tag suggestions, etc.
Types of machine learning are Supervised Learning,Unsupervised Learning and Reinforcement Learning.