Gradients2 SGD, Epochs, and Accuracy Testing Date : 2022.09.28 *The contents of this book is heavily based on Stanford University’s CS231n course. [Implementing SGD] The overall procedure is as the following: Create a batch of randomly selected data for training. Use the loss function to find optimal inputs for weights. Repeat the above to minimize prediction error. In step 2, we will be applying the gradient descent method to a random bat.. 2022. 10. 22. Loss Function and Stochastic Gradient Descent Date : 2022.09.23 *The contents of this book is heavily based on Stanford University’s CS231n course. [Data Modeling] The data modeling process can be separated into 2 major steps: Learning and Testing. In the learning process our goal is to establish a neural network with high precision. We can control a few variables that will affect the model. The first control variable is the Weight Variable.. 2022. 10. 20. 이전 1 다음 728x90 반응형
