Text Analysis Workshop
Practical introduction to text analysis, designed for those with Python experience. Join this workshop for a practical Introduction to Text Analysis, designed for those with Python experience (how to create functions, for loops, conditional logic, use the pandas library, etc.). The workshop covers Natural Language Processing (NLP) basics, API usage, data preparation, document/word embeddings, topic modeling, Word2Vec, Transformer models using Hugging Face, and ethical considerations. Students and researchers working in the digital humanities are especially encouraged to attend! CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2025-04-28-uwmadison-textanalysis/
Text Analysis Workshop
Practical introduction to text analysis, designed for those with Python experience. Join this workshop for a practical Introduction to Text Analysis, designed for those with Python experience (how to create functions, for loops, conditional logic, use the pandas library, etc.). The workshop covers Natural Language Processing (NLP) basics, API usage, data preparation, document/word embeddings, topic modeling, Word2Vec, Transformer models using Hugging Face, and ethical considerations. Students and researchers working in the digital humanities are especially encouraged to attend! CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2025-04-28-uwmadison-textanalysis/
WID Seminar Series
3rd Floor Orchard View Room, Discovery Building (Also offered online)Discovering simplicity in complex systems at the intersection of digital and natural worlds. ONLINE: https://uwmadison.zoom.us/j/96326864622
Text Analysis Workshop
Practical introduction to text analysis, designed for those with Python experience. Join this workshop for a practical Introduction to Text Analysis, designed for those with Python experience (how to create functions, for loops, conditional logic, use the pandas library, etc.). The workshop covers Natural Language Processing (NLP) basics, API usage, data preparation, document/word embeddings, topic modeling, Word2Vec, Transformer models using Hugging Face, and ethical considerations. Students and researchers working in the digital humanities are especially encouraged to attend! CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2025-04-28-uwmadison-textanalysis/
Sci-prov
Discovery Building 330 North Orchard Street, Madison, WI, United StatesScience Meets Improv ComedyJoin the Illuminating Discovery Hub and Amalgam Improv for an evening fusing science and spontaneous improv comedy like no other at Sci-Prov!Sci-prov combines science and improv in creative, funny, and never before seen ways. Scientists present their work in short, digestible presentations followed by brief Q&A, all of which can become fodder for the improv scenes. The improv scenes are created on the fly & unique to each show.Light refreshments and cash bar available. Tickets are free and registration is requested to ensure adequate seating.Parking: The closest parking ramps to the Discovery building are Lot 80 (Union South), [...]
Text Analysis Workshop
Practical introduction to text analysis, designed for those with Python experience. Join this workshop for a practical Introduction to Text Analysis, designed for those with Python experience (how to create functions, for loops, conditional logic, use the pandas library, etc.). The workshop covers Natural Language Processing (NLP) basics, API usage, data preparation, document/word embeddings, topic modeling, Word2Vec, Transformer models using Hugging Face, and ethical considerations. Students and researchers working in the digital humanities are especially encouraged to attend! CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2025-04-28-uwmadison-textanalysis/
Intro to Deep Learning with Keras
Discovery Building 330 North Orchard Street, Madison, WI, United Stateshttps://uw-madison-datascience.github.io/2025-05-19-uwmadison-DeepLearningKeras/
Intro to Deep Learning with Keras
Orchard View Room, Discovery BuildingHands-on introduction to the first steps in deep learning. This introduction covers the basics of deep learning in a practical and hands-on manner, so that upon completion, you will be able to train your first neural network and understand what next steps to take to improve the model. We start with explaining the basic concepts of neural networks, and then go through the different steps of a deep learning workflow. CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2025-05-19-uwmadison-DeepLearningKeras/
Intro to Deep Learning with Keras
Orchard View Room, Discovery BuildingHands-on introduction to the first steps in deep learning. This introduction covers the basics of deep learning in a practical and hands-on manner, so that upon completion, you will be able to train your first neural network and understand what next steps to take to improve the model. We start with explaining the basic concepts of neural networks, and then go through the different steps of a deep learning workflow. CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2025-05-19-uwmadison-DeepLearningKeras/
Intro to Deep Learning with Keras
Orchard View Room, Discovery BuildingHands-on introduction to the first steps in deep learning. This introduction covers the basics of deep learning in a practical and hands-on manner, so that upon completion, you will be able to train your first neural network and understand what next steps to take to improve the model. We start with explaining the basic concepts of neural networks, and then go through the different steps of a deep learning workflow. CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2025-05-19-uwmadison-DeepLearningKeras/
Intro to Deep Learning with Keras
Orchard View Room, Discovery BuildingHands-on introduction to the first steps in deep learning. This introduction covers the basics of deep learning in a practical and hands-on manner, so that upon completion, you will be able to train your first neural network and understand what next steps to take to improve the model. We start with explaining the basic concepts of neural networks, and then go through the different steps of a deep learning workflow. CONTACT: facilitator@datascience.wisc.edu URL: https://uw-madison-datascience.github.io/2025-05-19-uwmadison-DeepLearningKeras/
