Unsupervised Learning, the fourth lab of the Machine Learning and Deep Learning Series, participants will learn to work with unlabeled data using unsupervised learning techniques. The lab will explore clustering methods, including k-Means and hierarchical clustering, to uncover patterns in datasets. Participants will also learn dimensionality reduction techniques like Principal Component Analysis (PCA) to simplify high-dimensional datasets.
Regression, the third lab of the Machine Learning (ML) and Deep Learning Series will cover ML models for regression tasks. The session begins with the fundamentals of linear regression and progresses to polynomial regression and regularization methods such as Lasso and Ridge regression. In addition, decision trees, support vector machines and K-nearest neighbors (KNN) will be introduced to demonstrate their effectiveness in regression tasks.
Classification, the second lab of the Machine Learning and Deep Learning Series, shifts the focus to classification models for predicting categorical outcomes. Participants will explore a range of classification algorithms, starting from logistic regression and decision trees to more advanced models like support vector machines (SVMs), and k-nearest neighbors (KNN). Naive Bayes and other classifiers will also be covered to provide a comprehensive understanding of classification methods.
The first open lab of the Machine Learning and Deep Learning Series, this event sets the stage for understanding machine learning by providing a foundational overview of its core concepts and applications. Participants will explore the different types of machine learning—supervised, unsupervised, and reinforcement learning—and their use cases. This session is designed for those new to the field, with no coding experience required. It will also highlight how machine learning drives modern technological advancements and introduce the field of deep learning.
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 ASU Library's 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 to attend!
Presenters: Kerri Rittschof, Namig Abbasov and Abi Mercado Rivera.
Explore the history and contributions of the Hispanic/Latino community in Chandler, Arizona, featured in a new exhibit on display at the Polytechnic campus Library.
Want to create a stamp? Stop by ASU Library's Naturespace in Hayden Library to learn how to do a cut on a speedy carve block. Whether you are an expert or a beginner, any level of carving experience is welcome to join us for a morning of creativity.
Space is limited; reserve your spot today. Learn more about the Book Arts Studio and how you can schedule time to use the equipment!
Discover the unique and rustic canvases of nature as you paint on wood slices. Learn techniques, experiment with colors and create stunning, nature-inspired artwork that you can take home. Head over to ASU Library's Naturespace in Hayden Library to unleash your creativity and bring these natural canvases to life with vibrant colors and intricate designs.
Want to create a stamp? Stop by ASU Library's Naturespace in Hayden Library to learn how to do a cut on a speedy carve block. Whether you are an expert or a beginner, any level of carving experience is welcome to join us for a morning of creativity.
Space is limited; reserve your spot today. Learn more about the Book Arts Studio and how you can schedule time to use the equipment!
Are you interested in a relaxing sketching session surrounded by the library's natural history collection? Bring your art supplies and immerse yourself in a unique drawing experience at Naturespace, inside Hayden Library. Don't have art supplies? We've got you covered with drawing pencils and paper available on-site. Explore your creativity and connect with nature through art.