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Past In-Person Learning Experiences

 

Tuesday, February 16 - 4:30pm
Location: Virtual, Classroom
Instructor: Ricardo Henao

Natural language processing (NLP) is a field focused on developing automated methods for analyzing text, and also for computer-driven text generation (synthesis, for example in translation and text summarization).

Monday, February 8 - 12:00pm
Location: Virtual, Classroom
Instructor: David Carlson

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.

Tuesday, November 10 - 4:30pm
Location: Virtual, Classroom
Instructor: Nita Farahany

Artificial intelligence (AI) can reduce costs, improve efficiency, and potentially improve accuracy in many critical areas of life that impact humans. And yet, many of the tools of AI lack transparency, have inherent biases, and are difficult to govern.

Thursday, November 5 - 4:30pm
Location: Virtual, Classroom
Instructor: Lawrence Carin

This session will examine the multiple ways in which data science is playing a role in the transformation brought on by financial technology (FinTech). The discussion will review financial innovation, financial products and services, and how these are being impacted by data science.

Thursday, November 5 - 4:30pm
Location: Virtual, Classroom
Instructor: Akshay Bareja

Deep learning has emerged as a powerful approach to address complex problems in various fields, including biology. In this four-part series of vLEs, we will describe the theory and application of two deep learning models - the multiplayer perceptron and the convolutional neural network.

Wednesday, November 4 - 4:30pm
Location: Virtual, Classroom
Instructor: Jon Reifschneider

Once considered to be niche technologies limited to the domain of academic research and the few large global tech companies, today machine learning and AI are finding innovative application in almost every industry by companies of every size.

Thursday, October 29 - 4:30pm
Location: Virtual, Classroom
Instructor: Akshay Bareja

Deep learning has emerged as a powerful approach to address complex problems in various fields, including biology. In this four-part series of vLEs, we will describe the theory and application of two deep learning models - the multiplayer perceptron and the convolutional neural network.

Tuesday, October 27 - 4:30pm
Location: Virtual, Classroom
Instructor: Ricardo Henao

Generative adversarial networks (GANs) are a new tool in machine learning, that leverage advances in deep neural networks. Using GANs, one can develop a computer model that is capable of synthesizing highly realistic images, such as human faces and interesting art.

Thursday, October 22 - 4:30pm
Location: Virtual, Classroom
Instructor: Akshay Bareja

Deep learning has emerged as a powerful approach to address complex problems in various fields, including biology. In this four-part series of vLEs, we will describe the theory and application of two deep learning models - the multiplayer perceptron and the convolutional neural network.

Tuesday, October 20 - 4:30pm
Location: Virtual, Classroom
Instructor: William Adair

Professors Jun Yang (computer science) and Bill Adair (journalism and public policy) will discuss their work in automated fact-checking.