Machine Learning, Deep Learning, Neural Networks, Heartbeat, Mlops.
26 parameters. By using these two approximations, we can calculate the predicted value of ‘y’, and then by using the gradient descent algorithm, we can learn the parameters that are best suited for the given data, i.e… the squared error loss for training data would be at its minimum. Once we know