Dive into a 32-minute tutorial on building a fashion recognizer using PyTorch, led by core contributor Dmytro Dzhulgakov. Explore PyTorch's core functionality, tackle a classification problem, define network architecture, set up loss functions and optimizers, integrate TensorBoard, and construct a training loop. Gain hands-on experience with one of the most popular open-source machine learning frameworks, accelerating your journey from research to production deployment. Access additional resources including PyTorch tutorials, TorchVision documentation, and the PyTorch GitHub repository to further enhance your learning experience.
Intro to PyTorch Tutorial - Building Fashion Recognizer
Overview
Syllabus
] PyTorch Core functionality introduction.
] Demo: classification problem.
] Demo: Define network architecture.
] Demo: Define loss function & optimizer.
] Demo: Setting up TensorBoard.
] Demo: Training Loop.
Taught by
Microsoft Developer
