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    TRAINING AND LEARNING

                      For machines to become smart, they need to learn. This process is called training
                      and learning. Training and Learning in AI are the processes that help machines get

                      smarter and more accurate over time. They are the key parts of how AI systems
                      improve over time. Here's how they work:

                        Training: This is the process  where an AI

                         system  is taught  using large amounts  of
                         data. During training, the system is exposed
                         to examples that help it understand patterns

                         and make decisions.

                         For example: Training  an AI to  recognise
                         handwriting  involves  showing  it  many
                         examples  of different  handwritten  letters.  Over time,  the  AI learns how to

                         recognise letters even if they are written in different styles. The more data it
                         receives, the better it gets at understanding and recognising patterns.

                                                                         Learning: After the training  phase, AI
                                                                         systems can begin to learn from new data

                                                                         they encounter. This is known as learning.
                                                                         The  more data  the system  is exposed
                                                                         to, the better it becomes at completing
                                                                         tasks and making decisions. In machine

                                                                         learning, the system continues to improve
                                                                         by adjusting itself based on what it learns
                                                                         from the data.

                         For example: Once trained  to  recognise  cats  in photos, the AI continues  to
                         improve as it encounters new images. If it sees a new type of cat, it learns to
                         recognise that too, based on the features it has learned from previous data.

                          In simple terms, training is like teaching an AI using lots of examples and learning
                         is  how it  gets  better  over time  by  applying  what it  has been  taught  to  new
                         situations. Through these processes, AI systems become more accurate, reliable

                         and capable of performing complex tasks.

                                                                 Ask
                                                                           AGENT
                                                            OrangeAI
                        Which types of data are commonly used to train AI systems?

                               Study

                       12        Artificial Intelligence (CT & AI)-V

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