Designing and developing algorithms according to the behaviours based on empirical data are known as Machine Learning. While artificial intelligence in addition to machine learning, it also covers other aspects like knowledge representation, natural language processing, planning, robotics etc.
In the context of a machine learning interview question, the difference between “artificial learning” and “machine learning” could be interpreted in various ways, depending on the interviewer’s perspective or the specific terminology they are using. Here’s a breakdown of potential interpretations and answers:
- Interpretation 1: Artificial Learning vs. Human Learning
- In this interpretation, “artificial learning” could refer to the learning processes employed by machines or artificial intelligence systems, while “machine learning” specifically refers to the subfield of artificial intelligence that focuses on algorithms and models that allow computers to learn from data.
- Answer: “Artificial learning generally encompasses any learning process exhibited by machines or artificial systems. Machine learning is a specific subset of artificial learning, focusing on algorithms and techniques that enable computers to learn from data and improve performance on a task without being explicitly programmed.”
- Interpretation 2: Different Terms for the Same Concept
- Some interviewers might use “artificial learning” and “machine learning” interchangeably, viewing them as synonymous terms for the process of machines learning from data.
- Answer: “Artificial learning and machine learning are often used interchangeably to describe the process by which machines learn from data to improve performance on tasks. Both terms refer to the utilization of algorithms and techniques that enable computers to learn patterns and make predictions or decisions based on input data.”
- Interpretation 3: Artificial Learning as a Broader Concept
- Alternatively, the term “artificial learning” might be seen as a broader concept that encompasses not only machine learning but also other forms of artificial intelligence learning techniques such as evolutionary algorithms, reinforcement learning, or even expert systems.
- Answer: “Artificial learning encompasses a wide range of techniques used by machines to acquire knowledge and improve performance. While machine learning is a subset of artificial learning focusing on data-driven approaches, artificial learning can also include other methods such as evolutionary algorithms, reinforcement learning, and expert systems.”
It’s important to clarify the interviewer’s intended interpretation before providing an answer to ensure that your response aligns with their expectations.