The Duke+Data Science program (+DS) is pleased to announce a virtual offering of the Duke Machine Learning School for summer 2021, which will be held June 14-17.

The 3.5 day curriculum in the Machine Learning Virtual Summer School (MLvSS) is targeted to individuals interested in learning about machine learning, with a focus on recent deep learning methodology. The MLvSS will introduce the mathematics and statistics at the foundation of modern machine learning, and provide context for the methods that have formed the foundations of rapid growth in artificial intelligence (AI). Additionally, the MLvSS will provide hands-on training in the latest machine learning software, using the widely used (and free) PyTorch framework.

Learn more and register here

The broad areas of emphasis for the three-and-a-half-day class are as follows:

Monday, June 14 (9:00 AM – 4:00 PM Eastern Time):

  • Basic concepts in machine learning
  • Introduction to model building and the multi-layered perceptron (MLP)
  • Scaling to “big data” with stochastic gradient descent
  • Backpropagation as an efficient computation method
  • Case study applications of machine learning to digital health

Tuesday, June 15 (9:00 AM – 4:00 PM):

  • Image analysis with convolutional neural networks (CNNs)
  • Deep convolutional neural networks
  • Image segmentation, object detection, and object localization
  • Case study in image analysis and adversarial techniques with deep neural network (DNN) models

Wednesday, June 16 (9:00 AM – 4:00 PM):

  • Methods for natural language processing
  • Word embeddings
  • Recurrent neural networks
  • Temporal convolutional neural networks
  • Transformer networks
  • Case study of ethical and policy challenges in machine learning, including bias, transparency, and accountability

Thursday, June 17 (half day, 9:00 AM – 12:00 PM):

  • Data synthesis, with an emphasis on images
  • Generative adversarial network (GAN)
  • Deep networks for GAN
  • Learning and applications for GAN
Date & Time
Monday, Jun 14, 2021 - 9:00 am to Thursday, Jun 17, 2021 - 12:00 pm

Location: Virtual
Time: 9:00 am to 4:00 pm