Machine Learning & AI

It is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop a conventional algorithm for effectively performing the task.

Meaning of Machine Learning and AI: AI falls under the category of computer science which simply means augmenting the capability of machines in contrast with the human intelligence to accomplish a task or solve a problem. Machine Learning is a modern-day application of AI describes as a way to achieve AI which provides machines the ability to learn automatically without being explicitly programmed.

The technology involved in Machine Learning verses AI: AI refers to the technology designed to surpass the abilities of machines to think like humans, mostly in computational systems. Machine learning, on the other hand, is based on the idea that systems can act and learn from data that is either unstructured or unlabeled.

Function of Machine Learning and AI: The term AI is applied to when a machine mimics human cognitive functions for thinking, problem solving, memory, perception, and decision making.

Few Examples where Machine Learning is being used in our daily life:

Examples of Machine Learning:

  • Online Customer Support
  • Email Spam and Malware Filtering
  • Product Recommendations
  • Online Fraud Detection
  • Virtual Personal Assistants


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