Basics of AI: accuracy, epochs, learning rate, batch size and loss

Basics of AI: accuracy, epochs, learning rate, batch size and loss

HomeProf. Ryan AhmedBasics of AI: accuracy, epochs, learning rate, batch size and loss
Basics of AI: accuracy, epochs, learning rate, batch size and loss
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In this video we discuss the basics of AI training, such as learning rate, epochs, and batch size.

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Epochs: Just like humans, AI learns overtime and its intelligence increases as we continuously feed it training data. An Epoch means that AI has been fed the entire data set once.

Batch size: When training AI, we typically do not input the entire data set into the AI model due to computation and memory limitations.
Therefore, we generally split the training data into smaller batches that are added to the model separately. An era contains one or more batches.

Learning Rate: The learning rate represents the size of steps taken and indicates how aggressively you want to train the AI.
As the learning rate increases, the area covered in the search space will increase, so we can reach the goal (global minimum) faster. However, we may overshoot the target. At small learning rates, training will take much longer to reach optimized weight values.

I hope you will enjoy this video

Thanks and happy learning!

#BatchSize #LearningRate #Epochs

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