Gradient stream, also known as gradient descent, is an optimization algorithm used in machine learning and mathematical optimization to minimize a function by iteratively moving in the direction of steepest descent. The algorithm works by computing the gradients of the function with respect to the parameters and moving in the opposite direction of the gradients to minimize the function. Gradient stream is widely used in deep learning for training neural networks and is known for its simplicity and efficiency. The algorithm has several variants such as stochastic gradient descent, mini-batch gradient descent, and Adam optimization.
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