REGISTRATION NOTES
Click register and then use your @berkeley.edu or @lbl.gov email address.
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Location: Remote via Zoom.
Recordings: This D-Lab workshop will be recorded and made available to UC Berkeley participants for a limited time. Your registration for the event indicates your consent to having any images, comments and chat messages included as part of the video recording materials that are made available.
Start Time: D-Lab workshops start 10 minutes after the scheduled start time (“Berkeley Time”). We will admit all participants from the waiting room at that time.
Date & Time: This workshop runs from 2pm-5pm on:
- Tuesday, March 4
Description
In this workshop, we will convey the basics of deep learning in Python using keras on image datasets. You will gain a conceptual grasp of deep learning, work with example code that they can modify, and learn about resources for further study.
We start with a review of what deep learning is and then unpack what neural networks are and how they work. We then jump straight into Python, using the Keras library to build neural networks. We will explore how different architectures affect performance of predicting handwritten digit images.
Prerequisites: We recommend attending Python Fundamentals, Python Data Wrangling, and Python Machine Learning Fundamentals prior to this workshop.
Software Requirements: Installation Instructions for Python Anaconda
Workshop Materials: https://github.com/dlab-berkeley/Python-Deep-Learning
Questions? Email: dlab-frontdesk@berkeley.edu