Artficial neurons Core of deep learning are neural networks: mathematical entities capable of representing complicated functions through a composition of simpler functions. The basic building block of these complicated functions is the neuron
2020-10-26
import torch Learning is just parameter estimation Given input data corresponding desired outputs (ground truth) initial values for the weights The model is fed input data (forward pass) A measure of the error is evaluated by comparing the resulting outputs to the ground truth In order to optimize the parameter of the model (its weights) The change in the error following a unit change in weights (that is, the gradient of the error with respect to the parameters) is computed using the chain rule for the derivative of a composite function (backward pass) The value of the weights is then updated in the direction that leads to a decrease in the error The procedure is repeated until the error, evaluated on unseen data, falls below an acceptable level.
2020-10-24
import torch Images An image is represented as a collection of scalars arranged in a regular grid with a height and a width (in pixels). grayscale image: single scalar per grid point (the pixel) multi-color image: multiple scalars per grid point, which would typically represent different colors.
2020-10-21
import torch The world as floating-point numbers Neural networks transform floating-point representations into other floating- point representations. The starting and ending representations are typically human interpretable, but the intermediate representations are less so.
2020-10-19
Pretrained Network for Object Recognition Use pretrained network in TorchVision The TorchVision project contains a few of the best-performing neural network architectures for computer vision, such as AlexNet (http://mng.bz/lo6z) ResNet (https://arxiv.
2020-10-18
Summary of the book 'Deep Learning with PyTorch' officially released by PyTorch.
2020-10-18
Dive into the details of PyTorch.
2020-09-25
Log and visualize neural network training with TensorBoard.
2020-09-22
A tutorial for building and training a real image classifier.
2020-09-10
A tutorial which introduces the fundamental concepts of PyTorch through self-contained examples.
2020-09-10