Short course information:

This short course is devoted to an elementary introduction to machine learning.  The course is accessible to graduate students who have basic knowledge of multivariable calculus, linear algebra and numerical analysis. 

Lecture 1: Scientific Machine Learning

 

Lecture 2: Deep Neural Networks

  • Speaker: Jinchao Xu, Penn State
  • Abstract: This lecture will give an introduction to models,  algorithms and theories for both classic statistical learning and deep learning. Possible topics include:
    1. Elements of machine learning and historic developments
    2. Classic linear models:  logistic regression and support vector machine
    3. Deep neural network functions and approximation properties
    4. Convolutional neural networks (LeNet, AlexNet, VGG, ResNet, DenseNet, MgNet)
    5. Stochastic gradient descent method and convergence analysis
Skip to toolbar