HomeUpcoming webinars

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

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
Tuesday May 30, 11AM ET
View More Webinars

Register for the webinar

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.


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 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.

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. 

Presenter Bio

Maham Khan Headshot
Maham KhanSenior Data Science Content Developer at DataCamp

Maham is a Senior Data Science Content Developer at DataCamp, on a mission to make data skills accessible for everyone.

Before joining DataCamp, she worked as a Data Scientist at the World Bank, exploring applications of data science for disaster risk reduction, poverty alleviation and climate change mitigation.

She has a background in Experimental Psychology and Philosophy from the University of Oxford, and Urban Data Science from New York University.

View More Webinars