Various Optimization Algorithms For Training Neural Network

Many people may be using optimizers while training the neural network without knowing that the method is known as optimization. Optimizers are algorithms or methods used to change the attributes of your neural network such as weights and learning rate in order to reduce the losses. How you should change your weights or learning rates of your neural network to reduce the losses is defined by the optimizers you use. Optimization algorithms or strategies are responsible for reducing the losses and to provide the most accurate results possible. We'll learn about different types of optimizers and their advantages: Gradient Descent is the most basic but most used optimization algorithm.