Understanding the difference between the two most interchangeably used words machine learning and artificial intelligence.
So what is machine learning?
Machine learning is the subset of Artificial intelligence and not a synonym for artificial intelligence. Machine learning is the study of computer algorithms. Machine learning algorithms are needful in the advanced computerized world.
Machine learning is closely related to computational statistics. Machine learning is that field of artificial intelligence which learns for itself. Machine learning focuses on the event of computer programs which will access data . Machine learning involves computers discovering how they will perform tasks without being explicitly programmed to try to do that particular task. The process of learning begins with observations or data, like examples, direct experience, or instruction, so as to seem for patterns in data and make better decisions in the future supporting the examples that we offer the computer. The primary aim is to allow the computers to learn automatically without human interference or help and adjust actions accordingly. Machine learning enables analysis of mass quantities of data. It generally delivers faster, more appropriate results in order to identify profit making opportunities or costly risks, it may also require additional time and resources to train it properly.
Machine learning methods are categorized in four forms:
1) Supervised machine learning algorithms -
It applies that what has been learned in the past to new data using labeled examples to predict future events.
2) Unsupervised machine learning algorithms -
It is used when the information used to train is neither classified nor labeled. Unsupervised learning studies how systems can infer a function to explain a hidden structure from unlabeled data.
3) Semi-supervised machine learning algorithms -
It falls somewhere between first and second form that is supervised and unsupervised learning, because they use both labeled and unlabeled data for training – typically alittle amount of labeled data and an outsized amount of unlabeled data. The systems that use this method are ready to considerably improve learning accuracy.
4) Reinforcement machine learning algorithms-
It's a learning method that connects with its environment by producing actions and discovers defaults or rewards. This was a briefing about machine learning.
So now what is Artificial Intelligence?
Artificial Intelligence was first coined in 1956 but it became famous today because of advanced mechanization and advanced technology. Artificial Intelligence is a broad concept which has many sublets. Machine learning is such one sublet of artificial intelligence. It is also called as AI technology (Artificial Intelligence technology). Artificial intelligence is one of the trending career prospect of data science students. Artificial intelligence is basically the intelligence demonstrated by machines in contrast to natural intelligence demonstrated by humans or animals. The term "artificial intelligence" is often used to describe machines or electronic devices like computers or laptops that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving". Computer science as defined Artificial intelligence as “intelligent agents”. Artificial intelligence (AI) makes it possible for machines to learn quickly from experience ,exposure and adjust to new inputs and perform human-like tasks. Artificial intelligence is predicated on the principle that human intelligence are often defined during a way that a machine can easily mimic it and execute tasks, from the foremost simple to those that are even more complex. The goals of AI include learning, reasoning, and perception.As technology advances, previous benchmarks that defined AI become outdated. AI is continuously evolving to profit many various industries. There are various applications of AI technology in various fields of life.
Now, it's time to understand the difference between these two terms:
Artificial intelligence and machine learning are the part of computer science that are usually correlated with each other. These two technologies are the most trending technologies which are used for creating intelligent systems .Although these are two related technologies and sometimes people use them as a synonym for each other, but still both are the two different terms in various cases .Artificial Intelligence is like a tree with many branches and machine learning is a one of the important branch of that tree. Artificial intelligence is a broad and old concept having its roots affixed in 1956 whereas machine learning is a narrow and not much old concept. AI is a bigger concept to create intelligent machines that can simulate human thinking capability and behavior, whereas, machine learning is an application or subset of AI that allows machines to learn from data without being programmed explicitly.
The Key Difference between Artificial Intelligence and Machine Learning Can be understood by the following points:
AI is a technology that enables a machine to simulate human behavior. Machine learning is a subset of AI which allows a machine to automatically learn from past data without programming explicitly.
The goal of AI is to form a sensible computing system like humans to unravel complex problems .The goal of ML is to permit machines to find out from data in order that they will give accurate output.
In AI, we make intelligent systems to perform any task sort of a human. In ML, we teach machines with data to perform a particular task and give an accurate result.
Machine learning and deep learning are the two main subsets of AI. Deep learning is a main subset of machine learning.
AI has a very wide range of scope. Machine learning has a limited scope.
AI is functioning to make an intelligent system which may perform various complex tasks. Machine learning is functioning to make machines which will perform only those specific tasks that they're trained.
AI system is concerned about maximizing the chances of success.Machine learning is mainly concerned about accuracy and patterns.
The main applications of AI are Siri, customer support using catboats, Expert System, Online game playing, intelligent humanoid robot, etc. The main applications of machine learning are Online recommender system, Google search algorithms, Facebook auto friend tagging suggestions, etc.
On the basis of capabilities, AI can be divided into three types, which are, Weak AI, General AI, and Strong AI. Machine learning can also be divided into mainly three types that are Supervised learning, Unsupervised learning, Semi –Supervised learning and Reinforcement learning.
It includes learning, reasoning, and self-correction.It includes learning and self-correction when introduced with new data.
AI completely deals with Structured, semi-structured, and unstructured data. Machine learning deals with Structured and semi-structured data.
So from the following points it is very clear that words Artificial Intelligence and Machine learning are two different terms and not synonyms.