¡Hola, Mundo!

Backpropagation Whereas Logistic Regression is made of a single layer of weights, Neural Networks are made of many layers with non-linear activation. We need to have a mechanism to update the weights of the neurons using the gradient of the loss. Such a mechanism is called Backpropagation. It propagates the gradient from the last layer to the first one. chain rule It allows you to decompose the ..

VGG16 Visual Geometry Group 16 Layers deep. A convolutional neural network that is 16 layers deep. Initially, VGG is a model designed to study how the depth of neural networks affects. So, the filter size of the convolution layer was fixed at the smallest 3x3. This is because if the filter size is large, the image size quickly becomes small and it is difficult to make the depth. Models before VG..

argparse When there is a Python script called run.py , we can run the file at the command prompt as follows. $ ./run.py If you want your Python script to work differently depending on the options, you'll need to get these arguments through the command line such as below. $ ./run.py -d 1 -f It must parse the arguments(ex, '-d', '-f') of the command line entered by the user, and then perform appro..

GradientTape It records intermediate processes of functions, operations on Tape one by one. In other words, computational operation is saved in Tape. Reverse mode automatic differentiation TensorFlow calculates the differentiation of x for the loss by using the Reverse mode automatic differentiation with dx = tape.gradient(loss, x) Backpropagate the differential of x for the loss, repeat the tas..

Derivative The slope at a point. The rate of change of the function. HTML 삽입 미리보기할 수 없는 소스 Slope(Gradient of a line) A line is a number that describes both the direction and the steepness of the line. Polynomial Function Derivative Using the Factorization above, derive a derivative for the polynomial function below. Product Rule https://m.blog.naver.com/heoyoonhomath/223007374901 https://blog.na..