MACHINE LEARNING

Detailed explanation-1: -Gradient Descent is known as one of the most commonly used optimization algorithms to train machine learning models by means of minimizing errors between actual and expected results. Further, gradient descent is also used to train Neural Networks.

Detailed explanation-2: -Gradient descent is commonly used in supervised learning but the question is whether it could be used in Unsupervised Learning.

Detailed explanation-3: -Gradient descent guarantees the best possible answer in one run of the algorithm It is an optimization algorithm that seeks to find the best parameters of a function Gradient descent works best for a convex optimization function Gradient descent requires the optimization function to be differentiable.

Detailed explanation-4: -Gradient descent is by far the most popular optimization strategy used in machine learning and deep learning at the moment. It is used when training data models, can be combined with every algorithm and is easy to understand and implement. Everyone working with machine learning should understand its concept.