Presented by: Helge Rhodin, PhD; Department of Computer Science; University of British Columbia
In this session, Prof. Álvarez will define a Gaussian process (GP) model and describe how it is used to tackle (non-linear) regression problems including defining the kernel function, the key function that defines the Gaussian process.
Fabricio Lopes Sanchez, Sr. Cloud Solution Architect at Microsoft
John Brown, Sr. Cloud Solution Architect at Microsoft
Presented by Srinivas Turaga, PhD; Computation & Theory, HHMI Janelia Research Campus
In this session, we will work on a data visualization makeover exercise. We will start with a plot that would benefit from a thorough makeover and update it, step-by-step, using the ggplot2 package in R as well as a few other packages that play nicely with ggplot2.
In silico drug discovery approaches are becoming popular and cost-effective ways of identifying novel therapeutic candidates. In this vLE we will demonstrate how to use deep learning to predict drug-protein interactions.
In this session, you will learn how to participate in a Kaggle competition. Kaggle is an online community of data scientists and machine learning practitioners that frequently holds public competitions.
The convolutional neural network (CNN) represents the current state-of-the-art for image and video analysis, and is increasingly used for analyzing time series and other data with spatial or sequential
The basic concepts of machine learning are introduced with a focus on intuition and examples. The simpler and widely used logistic regression model is introduced first, and from this, multilayered neural network are introduced as a generalization.
In this one-hour virtual learning experience, 4 teams of Duke investigators will discuss their proposal concepts with data science experts.