Learn how to code a simple neural network using PyTorch in this step-by-step tutorial video. Explore the basic architecture of a fully connected network, create the network structure, handle data, implement loss functions, perform backpropagation, and evaluate model accuracy. Gain practical insights into tensor manipulation and making predictions with your trained model. Follow along with the provided code examples to build a solid foundation in neural network implementation using the PyTorch framework.
Overview
Syllabus
Introduction
Create Network
Data
Losstop backward
Check accuracy
Check predictions
Convert tensors
Checking accuracy
Taught by
Aladdin Persson
