In this Open Lab, Digital Humanities Analyst Namig Abbasov will utilize Python to navigate the key stages of quantitative data analysis in social science research. First, we will preprocess data, recoding and transforming necessary variables to ensure that the dataset is ready for statistical analysis. Subsequently, we will employ Python libraries to conduct Exploratory Data Analysis (EDA), making statistical graphs and various data visualizations to illustrate patterns, detect possible anomalies and understand overall data structure.
In the initial segment of this Open Lab, Digital Humanities Analyst, Namig Abbasov, will examine text analysis using unsupervised methods, focusing on topic modeling techniques. In the latter segment, we will investigate word embeddings, an increasingly popular approach for feature extraction in text analysis.
In this Open Lab, Digital Humanities Analyst,Namig Abbasov, will first quickly review the fundamentals of text analysis and then apply a range of supervised learning techniques, including linear and logistic regression, L1 and L2 regularization, cross-validation (CV), K-Nearest Neighbors (KNN) and Support Vector Machines (SVMs), to analyze text data.
There is more to learn! Building on the exploration of Unsupervised Machine Learning in the prior week, in this Open Lab, Digital Humanities Analyst Namig Abbasov, will cover association rule learning and reinforcement techniques and their applications. Time permitting, we will also conceptually examine semi-supervised learning.
Expanding upon the principles of Supervised Machine Learning, in this Open Lab, Digital Humanities Analyst Namig Abbasov, will cover machine learning techniques tailored for regression problems, along with the metrics used to evaluate these techniques. We will also examine ensemble learning methods as much as time allows.
Preparing responsibly open and accessible research data starts at the beginning of a project and continues through its completion. In this presentation, Research Data Initiatives Librarian Matthew Harp will provide standard practices and recommendations from planning to publishing that support transparent, open and reproducible research.
Data Science is an interdisciplinary field that uses the scientific method, processes, algorithms and systems to extract valuable meaning and insights from data. In this kickoff session, the Unit for Data Science and Analytics team will provide details of our upcoming events and opportunities to get involved in data science and analytics. Everyone is welcome!
Attention all players! Join Naturespace for the Octopus games, for the chance to win prizes by playing Red Light, Green Light with a twist. As the first game in the Octopus games, we have switched up the rules for a more nature-related experience. These rules will be shared during the game. In order to play fair, we cannot disclose any further information. To find out what these games are about, join us on the Hayden Library concourse level patio to test your ability and luck in Nature with the first of four games.
"Time and Change" is an exciting art exhibition dealing with creative cartography. Inspired by maps withdrawn from the ASU Library, students in the Art on Paper course, ASU School of Art, Herberger Institute for Design and the Arts have created an art exhibition focused on Time and Change. This marks the 10th anniversary of the Creative Cartography Student Exhibitions.
Have you ever sat outdoors and listened to the sounds around you? For this nature journaling exercise, Naturespace is going outside to listen to the sounds around the Tempe campus. We will create a soundscape map of the world of sounds and discuss our findings. Join us at Naturespace while we listen to the sounds of the Tempe campus. Bring a nature journal and explore with us.