Transfer Learning for Image Classification with PyTorch & Python Tutorial - Traffic Sign Recognition

Explore transfer learning for image classification using PyTorch and Python in this comprehensive tutorial focused on traffic sign recognition. Dive into dataset exploration, build a custom dataset, and create a model based on a pre-trained ResNet architecture. Learn to train and evaluate the model, make predictions on single images, and tackle the challenge of identifying unknown traffic signs. Gain practical experience in computer vision techniques and TorchVision implementation while developing a robust traffic sign classification system.

Dataset Overview
Exploring the data
Building a dataset
Creating a model based on pre-trained ResNet model
Training our model
Model evaluation
Predicting on a single image
Solving the unknown Traffic Sign problem