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Machine Learning Usecases 09-Transportation

Artificial Intelligence or AI is a special algorithm programmed to perform a particular function. Machine learning is a more narrow sub-niche of AI since the algorithm learns while performing operations and applying pre-defined parameters.
Machine Learning Usecases 09-Transportation

Machine learning uses algorithms to build a model based on data in order to make predictions or decisions that don’t involve human intervention and programming. These algorithms are used in a variety of applications where conventional algorithms are not enough to perform the needed tasks.

Machine learning can be approached in 3 different ways:

Supervised learning – this method implies the presentation of example inputs and their desired outputs to a computer with the main goal being to learn a general rule that maps inputs and outputs.

Unsupervised learning – the algorithm has no examples to learn from, it is left on its own to find structure in its input. This serves as a goal itself and a means toward an end.

Reinforcement learning – this implies that the computer interacts with a dynamic environment having to perform a specific goal, for instance, driving a vehicle, filling in data, playing a game, etc.

Probyto AI allows organizations to build and manage such usecases and track the benefits of AI adoption in their businesses. Currently, FREE 60 minutes AI Consultation is being provided to the registered users in the Probyto AI Demo platform. If you haven't registered yet, register now to Probyto AI Demo.

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