{"id":10023,"date":"2026-08-10T10:14:07","date_gmt":"2026-08-10T10:14:07","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-deep-learning-image-classification-in-pytorch-2-0-2023-11\/"},"modified":"2026-08-10T10:14:07","modified_gmt":"2026-08-10T10:14:07","slug":"udemy-deep-learning-image-classification-in-pytorch-2-0-2023-11","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-deep-learning-image-classification-in-pytorch-2-0-2023-11\/","title":{"rendered":"Udemy \u2013 Deep Learning Image Classification in PyTorch 2.0 2023-11"},"content":{"rendered":"
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Description<\/span><\/h2>\n

Deep Learning Image Classification in PyTorch 2.0 Course. This comprehensive course teaches you how to build advanced image classification systems using deep learning and the PyTorch 2.0 framework in Python 3. Throughout the course, you will learn the fundamentals of designing and training deep neural networks to detect objects in images. The material is presented in a step-by-step, hands-on manner, including installing essential libraries like Cuda and Cudnn to take advantage of GPU capabilities, working with Google Colab Notebook, and connecting it to Google Drive for data management. It also covers industry-standard techniques for data preparation and processing with the torchvision library, data augmentation with methods like resizing, rotating, and changing colors, and implementing a data pipeline with Data Loader. You will learn about different neural network architectures, including LeNet, VGG16, Inception v3, and ResNet50, and analyze each model layer by layer. Additionally, topics such as implementing training and inference pipelines, transfer learning for working with limited data, and displaying model results on images are covered. By the end of the course, you will be able to design and build efficient image classification models, a skill that is useful in various fields such as image processing and machine vision. This course is designed for those interested in deep learning, from beginners to experts, and provides the knowledge necessary to enter the field.<\/span><\/p>\n

What you will learn:<\/span><\/h3>\n