Machine Learning and AI are the two predominant terms of Computer Science. These technologies are used for designing many intelligent systems. The present technological world is paying a lot of attention to Machine Learning and AI techniques. AI and Machine learning have more differences in their algorithms, approach, and logical terms. This article discusses the differences between Machine Learning and AI.

Machine Learning functions

Machine Learning is, extracting knowledge from the data.

Without being programmed, by using historical data, Machine learning allows the computer system to make a choice. Machine Learning can handle a huge amount of semi-structured and structured data. So that the model of machine learning can make a perfect prediction or produce perfect results based on that data.

Machine Learning is used in different areas like Google search algorithm, Email Spam filter, Facebook Auto friend tagging suggestion, etc. Join Machine Learning Training in Bangalore and learn more about the implementation of Machine Learning.

Artificial Intelligence functions

For the Artificial Intelligence System, instead of pre-programming, they use an algorithm that can run with their intelligence. It includes a machine learning algorithm such as deep learning neural networks and reinforcement learning algorithms. AI is being used in various areas like Siri, Google. Join an Artificial Intelligence Course in Bangalore and gain more knowledge about trending technology in the industry.

The Basic Difference Between Machine Learning and AI:

Machine Learning Artificial Intelligence
It is a subset of Artificial Intelligence. Machine Learning can support a machine to learn automatically from past data without programming explicitly. Artificial Intelligence technology allows a machine to act like human behavior.
Machine Learning’s aim is to support machines to learn from past data so that they can provide perfect output. The purpose of AI is to design a smart computer system to act and behave like humans to solve complicated problems.
The main subset of Machine Learning is Deep Learning. The two main subsets of AI are Deep Learning and Machine Learning.
Machine learning has only limited scope. Artificial Intelligence has a broad range of scope.
  Machine Learning is to design machines that can perform the specific tasks for which they are trained.   AI is to design an intelligence system. It can perform different complex tasks.
Machine Learning is essentially involved with pattern and accuracy. AI systems are mainly involved with maximizing the chances of success.
Machine Learning applications are Google Search Algorithms, Online recommender systems. etc. The applications of AI are Expert System, Online game playing, Siri, Intelligence humanoid, robot.
Machine Learning is classified into three types:
  • Reinforcement Learning
  • Unsupervised Learning
  • Supervised Learning
AI is classified into three types:
  • Weak AI
  • General AI
  • Strong AI
Machine Learning includes self-corrections and self-learning when added with new data. AI can introduce self-correction, learning, reasoning.
Machine learning can completely deal with semi-structured and structured data. AI can deal with unstructured and semi-structured and structured data.
Without considering more about the optical solution, Machine Learning will continue after the solution. AI can help in detecting the optical solutions
Machine Learning leads to knowledge. AI leads to wisdom or intelligence

Machine Learning uses the experience to look for the pattern which is learned. Join Machine Learning Training in Chennai and gain more knowledge of the ML techniques.

Whereas AI uses the experience to acquire knowledge/skill and also know how to apply that knowledge in new environments. Learn the Artificial Intelligence Course in Chennai and acquire wider knowledge of AI technology. Both these technologies have a great demand and scope at present. Learn any of these technologies to secure your career.






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