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Machine Learning in Python - part 1/3 - Data Hub Tech Talk

Part 1, overview and introduction, of a 3-part introductory series on using Machine Learning and Artificial Intelligence with Python. We will discuss basic machine learning concepts with code examples, introducing concepts such as ensemble methods (random forests, gradient boosting), multi-level perceptrons (simple neural networks), and K-means clustering using the Python scikit-learn framework. Subsequent talks in this series will cover deep learning frameworks such as TensorFlow and PyTorch for natural language processing and computer vision tasks.

Date:
Tuesday, December 13, 2022
Time:
12:30pm - 1:30pm
Location:
Data Hub presentation / collaboration space
Campus:
University of Idaho - Moscow campus
Presenter:
Luke Sheneman
Categories:
Data Hub Library Workshop

Registration is required. There are 23 in-person seats available. There are 96 online seats available.

Upcoming Workshops

Time Zone: Pacific Time - US & Canada (change)

Nov
29
12:30pm - 1:00pm, Data Hub presentation / collaboration space, University of Idaho - Moscow campus.
Nov
30
12:00pm - 4:00pm, The MILL @ UIdaho Library, University of Idaho - Moscow campus.
Dec
6
12:30pm - 1:00pm, Data Hub presentation / collaboration space, University of Idaho - Moscow campus.
Dec
13
12:30pm - 1:30pm, Data Hub presentation / collaboration space, University of Idaho - Moscow campus.
Dec
15
3:00pm - 5:00pm, Main Library, University of Idaho - Moscow campus.