The Artificial Intelligence vs Machine Learning debate has been ongoing for some time now. AI and ML are two different types of technologies, each with separate applications. AI is a way to simulate human decision-making by using software algorithms. On the other hand, MI uses algorithms to analyze data to make predictions or solve problems without being programmed how to do so beforehand.
What should I know about this?
In AI, the system is programmed to find out solutions on its own by reasoning or trial and error based on specific algorithms. In contrast, when we talk about machine learning, the computer model does not have any prior knowledge of what to learn from but learns with experience. With AI, multiple tools are readily available for solving problems, including neural networks, genetic programming, etc. At the same time, ML has two primary approaches – supervised and unsupervised learning. In the supervised approach, everything depends upon labeled data sets. In contrast, in the case of the Unsupervised Approach, only unlabeled data sets are taken into account for training models.
We hope this information has been helpful to you.
