What is the correct description of how Machine Learning works?
A.
Machine learning works as any other computer program - by following a predefined sequence of instructions.
B.
Machine Learning works by gaining experience from looking at multiple examples, and then using that experience to solve the problem by making predictions.
C.
Machine learning works by mapping the input to the output based on a collection of algorithms stored in a relational database.
D.
Machine Learning works by searching for the correct answer in a huge database of possible answers.
Machine Learning (ML) is a subset of artificial intelligence that enables systems to learn from data, identify patterns, and make decisions with minimal human intervention. Unlike traditional programming, where a developer writes the instructions to solve a problem, ML algorithms learn from the data. They improve their performance as the amount of data increases. This learning process involves training an ML model on a dataset, allowing it to learn from the examples provided. Once the model is trained, it can make predictions or decisions based on new, unseen data. This approach is powerful in handling complex tasks where defining explicit rules is challenging.
References:
UiPath AI Center Guide: Introduction to Machine Learning
UiPath AI Fabric: Machine Learning Models
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