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 is a 2-part series that runs from 10am-1pm
- Wednesday, November 17
- Friday, November 19
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
This workshop introduces the basic concepts of Deep Learning — the training and performance evaluation of large neural networks, especially for image classification, natural language processing, and time-series data. Like many other machine learning algorithms, we will use deep learning algorithms to map input data to their appropriately classified outcome labels.
You will use the R interface to Keras to become familiar with basic concepts like input and output layers, batch sizes and output dimensions, dropout rates, weight parametrization and bias, backpropagation, and loss, activation, and optimization functions. You will also gain confidence exploring more complex approaches that utilize pretrained and fine-tuned models.
Prior knowledge requirements: D-Lab's Intro to Machine Learning in R workshop series or equivalent introductory machine learning knowledge.
Prerequisites: D-Lab's R Introduction to Machine Learning with tidymodels: Parts 1-2 series or equivalent introductory machine learning knowledge.
Workshop Materials:https://github.com/dlab-berkeley/Deep-Learning-in-R
Feedback: After completing the workshop, please provide us feedback using this form
Questions? Email: dlab-frontdesk@berkeley.edu