Please note: Everyone is placed on the waitlist at first. It may take up to 24 hours to confirm your UCB affiliation and then you will receive a confirmation email and calendar invite. You will need to finish your registration by filling out this form: https://dlab.berkeley.edu/affiliations
Location: Remote via Zoom. Link will be sent on the morning of the event.
Date & Time: This workshop runs from 9am-12pm on Wednesday, November 17.
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.
Description
In this workshop we start with a brief history of ANNs (Artificial Neural Networks) and an explanation of the intuition behind them. We introduce a conceptual understanding of ANNs with few mathematical barriers, and no programming requirements.
Next we provide a step-by-step construction of a very basic ANN. Although the code examples are written in Python, if you are familiar with another language such as R the examples are intuitive enough that you can follow along conceptually.
Finally we introduce the popular Python library called scikit-learn to implement an ANN to solve a classification problem. High-level libraries such as scikit-learn reduce the work for a researcher implementing ANNs, including tuning sets of parameters.
Prerequisites: D-Lab's Python Introduction to Machine Learning: Parts 1-2 or equivalent knowledge.
Workshop materials: https://github.com/dlab-berkeley/ANN-Fundamentals
Feedback: After completing the workshop, please provide us feedback using this form
Questions? Email: dlab-frontdesk@berkeley.edu