Join us for military-inspired literature readings at a virtual event to mark the launch of the second edition of ISSUED: Stories of Service. One lucky guest will win a copy of the first edition of ISSUED.
Learn more about this publication by visiting issuedjournal.com
Join the Office of Veteran and Military Academic Engagment for an online panel discussion, where local veterans share their experiences and insights on civic engagement.
Explore opportunities like working as a poll worker, volunteering with veteran organizations, joining a legislative caucus, performing jury duty and more.
In this Open Lab, Namig Abbasov, Digital Humanities Analyst, will first define the boundaries of discriminative AI, comparing it to generative AI. Then we will explore several techniques in discriminative AI and why they are discriminative. In the third part, we will cover discriminative techniques in deep learning and dive into Convolutional Neural Networks (CNNs), first demonstrating how they work and then outlining major architectures such as AlexNet, ResNet and EfficientNet as much as our time allows.
In this Sentiment Analysis with Python Open Lab, Namig Abbasov, Digital Humanities Analyst, will begin by explaining what sentiment analysis is and why it is a vital text analysis method for both the private sector and academic research.
Embark on an exciting journey as we explore the fascinating crossroads of literary analysis and data science! Recent advances in AI, large language models, and other advanced computational techniques have been revolutionizing literature studies across the board. Join us in our Open Lab to learn how you can take your first steps in using data science and analytics tools to enhance your literary analysis.
In this Open Lab, Digital Humanities Analyst Namig Abbasov will seek to answer questions such as “Machine age … stuff like that….” Many of us remember this quote from the “Push-Button Kitty” episode of our favorite childhood cartoon “Tom and Jerry,” where Tom’s human asks the cat to leave his job and hence the house as she gets a new mouse catcher, a robotic one. The episode was released in 1952.
In this Open Lab, Digital Humanities Analyst Namig Abbasov, will cover generative AI and large language models. We will first define what generative AI is and how it works. Attendees will learn about the differences between generative AI and discriminative AI, followed by an introduction to generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs).
The Numbers Don’t Speak for Themselves: Convey Your Story Using Data Visualization with Python
Are you struggling to find the best way to present a data set? Are you trying to find a way to create compelling data visualizations that can help you tell a story? Come find out how Python can help you.
The US does not support humanities research. Christopher Newfield has noted that the US funds humanities research to the tune of 1/20 of one percent of its national research budget. That's a problem for both faculty and students. But how can we expect the government or the culture in general to recognize the value of expertise in language, literature, writing, and culture if we cannot articulate what that expertise is or does?
Are you interested in learning how to code? Are you trying to find a free-to-use program to analyze your data? Are you a fan of low learning curves with high returns? Whether for a class, a personal project, your research, or just for personal interest, Python might be for you!