The main difference between AI and Machine Learning is that AI is the development of computer systems that are able to perform tasks intelligently, similar to a human being, while machine learning is a type of artificial intelligence that gives a system the ability to learn without being explicitly programmed.
Nowadays, technology is developing rapidly. Scientists and Engineers invent various technologies to improve the quality of life. One such technology is AI (Artificial Intelligence). Another term for AI is Machine Intelligence. It enables machines to perform tasks and make decisions similar to a human. In overall, AI is a wide area. Natural language processing and robotics are other fields that come under AI. On the other hand, machine learning is a subset of AI. Therefore, we can consider a machine learning application as an AI application as well.
Key Areas Covered
1. What is AI
-Definition, Functionality
2. What is Machine Learning
-Definition, Functionality
3. Difference Between AI and Machine Learning
-Comparison of key differences
Key Terms
Artificial Intelligence, Machine Learning
What is AI
AI or Artificial Intelligence is the technology that allows machines to mimic human behaviors. It allows a machine to learn from experience. They receive inputs and perform tasks similar to a human. Also, this technology is capable of processing a large amount of data and make decisions from them. In overall, AI is a field that combines multiple disciplines such as Computer Science, Mathematics, Engineering, and Computational Physics.
Fields such as Machine Learning, Deep Learning and Natural Language processing are subcategories of AI. Thus, it emphasizes that AI is a broad subject area. Furthermore, there are numerous amounts of AI-based applications. Games, self-driving cars, and industrial robots are some examples of AI. Also, it helps in developing applications related to medicine, manufacturing, autonomous vehicles and many more.
What is Machine Learning
Machine Learning is a subset of AI which uses statistical methods to enable machines to improve with experience. The machine learning algorithm is capable of identifying the patterns in the dataset and adjust the program action accordingly. In other words, it automates the analytical model building.
Machine learning life cycle consists of several steps. The first step is to collect data from various data sources such as excel sheets, databases, Twitter and Yahoo. The second step is to perform data wrangling. It is the process of filtering and cleaning the data. Thirdly, the data is analyzed. In this step, we create a model using the data. The fourth step is to train the algorithm, which involves allowing it to discover the patterns of the dataset. Next step is to test the algorithm to determine its accuracy. Finally, if the model is accurate, it is possible to deploy the application.
Furthermore, there are various types of machine learning, including supervised learning, unsupervised learning and reinforcement learning. Supervised learning allows the program to identify the patterns using a set of labelled data. In other words, these algorithms are capable of mapping the inputs to output depending on the example input and output pairs. Moreover, unsupervised learning allows the algorithm to identify patterns using unlabeled data. Finally, reinforcement learning allows an algorithm to learn from previous tasks.
Difference Between AI and Machine Learning
Definition
AI or Artificial Intelligence is the intelligence demonstrated by machines, similar to the natural intelligence displayed by humans, while machine learning is the scientific study of algorithms and statistical methods that computer systems use to perform a specific task effectively without using explicit instructions. Thus, this describes the main difference between AI and Machine Learning.
Functionality
Furthermore, AI focuses on mimicking the intelligent behavior similar to a human, whereas machine learning focuses on identifying the hidden patterns and on improving the accuracy of prediction.
Conclusion
AI and Machine Learning are two terms frequently used, but they have a difference. The main difference between AI and Machine Learning is that AI is the development of computer systems that are able to perform tasks intelligently similar to a human being, while Machine Learning is a type of Artificial Intelligence that gives a system the ability to learn without being explicitly programmed.
References:
1.“Artificial Intelligence.” Wikipedia, Wikimedia Foundation, 2 June 2019, Available here.
2.“Machine Learning.” Wikipedia, Wikimedia Foundation, 3 June 2019, Available here.
3.edureka! YouTube, YouTube, 25 Feb. 2019, Available here.
Image Courtesy:
1.”44405376514″ Mike MacKenzie via Flickr
2. “Machine learning process in summary” By EpochFail – Own work (CC BY-SA 4.0) via Commons Wikimedia
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