👉 In machine learning and computer science, an optimizer is a technique used to find the best hyperparameters for a model. It's like choosing the right size of the square in chess or the right amount of water to fill a fish tank. Optimizers are used to make these choices for a specific task.
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What is the definition of Optimizer? 🙋
👉 An optimizer in machine learning is a technique used to adjust the parameters of a neural network or other machine learning model so that it produces better predictions. The goal of an optimizer is to minimize the loss function, which is a measure of how well the model is performing on its training data. The most common types of optimizers include gradient descent, stochastic gradient descent (SGD), and adaptive gradient descent (Adagrad). These algorithms are used in various machine learning frameworks such as TensorFlow, PyT
