Machine Learning Artificial Intelligence Python Data Scientist

Sloth or Pastry? Using PyTorch and Deep Learning for Image Classification

In this session, using DataCamp Workspace we'll learn all about loading custom datasets into PyTorch and using transfer learning to perform an image processing task using a mostly-pretrained model, which we'll fine-tune.

Maham Khan

2023년 6월 1일

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Google로 계속하기계속 진행하시면 다음 사항에 동의하는 것으로 간주됩니다: 이용약관 및 개인정보 처리방침 그리고 귀하의 데이터가 미국에 저장된다는 점에 동의하는 것으로 간주됩니다.

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In the age of deep learning, data scientists and machine learning engineers seldom create and train neural networks from scratch. A big chunk of what goes into performing a machine learning task, however, is collecting, preparing, and loading data to feed into a model.

In this session, using DataLab we'll learn all about loading custom datasets into PyTorch and using transfer learning to perform an image processing task using a mostly-pretrained model, which we'll fine-tune.

We'll be using computer vision to answer the internet-popular question: is it a sloth or a pain au chocolat? This is a binary image classification task.

Key takeaways

Machine learning engineers seldom train models from scratch
Learning to load data is an important building block for deep learning in PyTorch
Models trained on billions of images are available at our disposal for transfer learning