1. PyTorch Computer Vision
  1. Computer Vision libraries
  1. Make predictions + Model 0 results
  1. Model 1: Better model with non-linearity
  1. Make and evaluate random predictions with best model
  1. Confusion matrix
  1. Model 0: Xây dựng mô hình baseline (Cơ sở)
  1. Compare model results and training time
  1. Chuẩn bị dataset
  1. Setup device agnostic-code
  1. Model 2: Building a CNN
  1. Prepare DatalLoader

Hình dạng input và output

Visualize hình ảnh

Setup loss, optimizer and evaluation metrics

Function to time our experiments

Training loop + Training model on batches

Loss,optimizer and evaluation metrics

Train and Test loop

7.3 Loss function, optimizer

7.2 Stepping through nn.MaxPool2d()

Train + Test

7.1 Stepping through nn.Conv2d()

  1. Save + load best peforming