Events

This workshop will provide an introduction to graphics in R with ggplot2. Participants will learn how to construct, customize, and export a variety of plot types in order to visualize relationships in data. We will also explore the basic grammar of graphics, including the aesthetics and geometry layers, adding statistics, transforming scales, and coloring or panelling by groups. You will learn how to make histograms, boxplots, scatterplots, lineplots, and heatmaps as well as how to make compound figures. Prerequisites: D-Lab’s R Fundamentals or equivalent knowledge; previous experience with base R is assumed. Registration: https://dlab.berkeley.edu/cas?destination=/events/r-data-visualization/2023-04-11 Workshop Materials: https://github.com/dlab-berkeley/R-Data-Visualization(link is external) Software Requirements:Installation Instructions(link is external) for R and RStudio Is RStudio Not working on your laptop?Attend the workshop anyway, we can provide you with a cloud-based solution(link is external) until you figure out the problems with your local installation.

The goal of this workshop is to build intuition for deep learning by building, training, and testing models in Python. Rather than a theory-centered approach, we will evaluate deep learning models through empirical results. 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. Lastly, we explore a specific flavor of neural networks, the convolutional neural network. We review how it’s different from a standard vanilla neural network, and build different architectures to test how well they perform on the classification of animal and vehicle image classification. Prerequisites: D-Lab's Python Machine Learning Fundamentals (6 hours) series or equivalent introductory machine learning knowledge. Registration: https://dlab.berkeley.edu/cas?destination=/events/python-deep-learning-parts-1-2/2023-04-11 Workshop Materials: https://github.com/dlab-berkeley/Python-Deep-Learning