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Introduction to Machine Learning: Neural Networks

In this workshop, participants will dive into the fascinating world of neural networks. Neural networks have emerged as powerful models for solving complex and nonlinear problems. This workshop begins with an introduction to neural networks, covering their architecture, activation functions, and training algorithms. Participants will gain insights into how neural networks can effectively capture and learn complex patterns in images, making them ideal for tasks like recognizing digits. They will also learn about the importance of preprocessing techniques and streamlining the preprocessing, training, and evaluation steps through pipelines. By the end of this workshop, participants will have a solid foundation in neural networks and the ability to build robust pipelines using Scikit-learn.
 
In this workshop, we will use cloud-based platforms, so you don’t need to have Python installed. Please make sure that you have a Google Colaboratory (https://colab.research.google.com/) account. This workshop will involve hands-on exercises that require the use of programming tools and libraries commonly used in machine learning, such as Python and Scikit-learn. As such, prior familiarity with Python programming is recommended for participants to fully benefit from the practical component of the workshop.

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Location Details

Location:
*ONLINE*

If you have any questions, concerns, or accessibility needs please email eka.grguric@ubc.ca.

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This event is online. Registrants receive the link 24 hours before the event. Registration closes at the same time.
Date:
Wednesday, October 25, 2023
Time:
12:00pm - 2:00pm
Categories:
  Digital Scholarship     Research Commons  
Presenter(s):
Vedant Bahel

Registration is required. There are 156 seats available.

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Presenter(s)

Vedant Bahel

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