Transfer Learning with ResNet18 on Sign Language MNIST | Hands on Machine Learning with PyTorch скачать в хорошем качестве

Transfer Learning with ResNet18 on Sign Language MNIST | Hands on Machine Learning with PyTorch

Welcome to another episode of Hands-on Machine Learning with PyTorch! In this video, we dive into Transfer Learning using the powerful ResNet18 model to classify American Sign Language (ASL) gestures from the Sign Language MNIST dataset. You'll learn how to: Load and preprocess the dataset Build a custom PyTorch Dataset class Fine-tune a pretrained CNN (ResNet18) Train, evaluate, and visualize performance Generate a detailed classification report and confusion matrix This project demonstrates how to adapt a state-of-the-art deep learning model to your own image data, even if it's grayscale and relatively small in size. Perfect for beginners and intermediate learners looking to get real-world exposure to computer vision and transfer learning! 👉 Don’t forget to Like, Share, and Subscribe for more PyTorch tutorials and machine learning content.