This course on PyTorch for Deep Learning aims to teach learners how to construct deep learning models using PyTorch and Python. By the end of the course, students will be able to build deep neural networks, perform image classification, and train generative adversarial networks (GANs) using PyTorch. The course covers PyTorch basics, linear regression, logistic regression, convolutional neural networks, and more. The intended audience for this course includes beginners in deep learning and neural networks who want to enhance their skills in using PyTorch for various applications.
Overview
Syllabus
Introduction.
PyTorch Basics & Linear Regression.
Image Classification with Logistic Regression.
Training Deep Neural Networks on a GPU with PyTorch.
Image Classification using Convolutional Neural Networks.
Residual Networks, Data Augmentation and Regularization.
Training Generative Adverserial Networks (GANs).
Taught by
freeCodeCamp.org
