/DeepLearning-Programming

PyTorch code for deep learning practice

Primary LanguageJupyter Notebook

DeepLearning-Programming

This repository aims to provide PyTorch code for deep learning practice of Andrew Ng's course.

Table of Contents

  1. Basics of Neural Network programming

    1-1. Basics of PyTorch tensors (Notebook)

    1-2. Load and preprocessing images using TensorFlow (Notebook)

    1-3. Load and preprocessing image using PyTorch (Notebook)

    1-4. Self-defined data loader using PyTorch (Notebook)

    1-5. Implementation of logistic regression (Notebook)

    1-6. Implementation of shallow neural network (Notebook)

    1-7. Regularization (L2 penalty and Dropout) (Notebook)