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Past In-Person Learning Experiences

 

Friday, November 19 - 12:00pm
Location: Virtual, Classroom
Instructor: Helge Rhodin

Presented by: Helge Rhodin, PhD; Department of Computer Science; University of British Columbia

Thursday, November 18 - 11:00am
Location: Virtual, Classroom
Instructor: Mauricio Álvarez

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.

Tuesday, November 2 - 4:00pm
Location: Virtual, Classroom
Instructor: Fabricio Lopes Sanchez

Presented by:
Fabricio Lopes Sanchez, Sr. Cloud Solution Architect at Microsoft
John Brown, Sr. Cloud Solution Architect at Microsoft

Wednesday, October 20 - 4:00pm
Location: Virtual, Classroom
Instructor: Srinivas Turaga

Presented by Srinivas Turaga, PhD; Computation & Theory, HHMI Janelia Research Campus

Tuesday, October 19 - 4:00pm
Location: Virtual, Classroom
Instructor: Mine Cetinkaya-Rundel

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.

Tuesday, October 12 - 4:00pm
Location: Virtual, Classroom
Instructor: Akshay Bareja

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.

Thursday, September 23 - 4:00pm
Location: Virtual, Classroom
Instructor: Akshay Bareja

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.

Tuesday, September 21 - 12:00pm
Location: Virtual, Classroom
Instructor: Timothy Dunn

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

Tuesday, September 14 - 4:00pm
Location: Virtual, Classroom
Instructor: Ricardo Henao

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.

Thursday, June 10 - 11:00am
Location: Virtual, Classroom
Instructor: Maciej Mazurowski

In this one-hour virtual learning experience, 4 teams of Duke investigators will discuss their proposal concepts with data science experts.