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May 2022
Boosting Python for High Performance Data Analytics (2) DataFrame Game
While Python becomes the most popular programming language since 2019, data scientists often have a few common complaints about its slow speed and the limited capabilities of handling the big data scenarios. In this workshop series, we will present an extensive discussion on how to improve the performance of Python in data science by looking under the hood of its language/libraries and using the technologies to make Python a practical solution for the high-performance big data analytics. In the second…
Find out more »Hoffman2 Happy Hour: Running non interactive applications on the Hoffman2 Cluster (batch jobs) + Q&A
The Hoffman2 Happy Hours are designed to showcase one cluster related topic in a short presentation (no more than 20 minutes and generally much less) or lightning talk format, to be followed by 30 to 40 minutes of discussion and user support (office hour style). Each Hoffman2 Happy Hour meeting is 50 minutes long. Bring your computational questions (they do not have to be strictly related to the topic of the week) or just your curiosity. Examples and hands-on components…
Find out more »R Graphics: Introduction to ggplot2
This seminar teaches the “grammar” of graphics that underlies the ggplot2 package, allowing the user to build eye-catching, publication-quality graphics layer-by-layer. We cover the basic elements of the grammar of graphics, including aesthetics, geoms, scales, and themes, and we will show you how easy ggplot2 makes it to integrate these elements to make informative and beautiful graphics. The seminar is meant to be interactive with attendees participating in the coding, so some very basic R coding knowledge is helpful but…
Find out more »What is Causal Inference and Where is Data Science Going?
Speaker: Judea Pearl Professor UCLA Computer Science Department University of California Los Angeles Date and Time:May 27, 2022 @12:00 PM (PST) Location: Zoom Registration: https://ucla.zoom.us/meeting/register/tJEscOugpzMoHNWEBVGRezm715JHi6fJCQoo Abstract: The availability of massive amounts of data coupled with an impressive performance of machine learning algorithms has turned data science into one of the most active research areas in academia. UCLA is no exception. The past few years, however, have uncovered basic limitations in the model-free direction that data science has…
Find out more »Hoffman2 Happy Hour: Array jobs: run multiple jobs of the same type from one submission script + Q&A
The Hoffman2 Happy Hours are designed to showcase one cluster related topic in a short presentation (no more than 20 minutes and generally much less) or lightning talk format, to be followed by 30 to 40 minutes of discussion and user support (office hour style). Each Hoffman2 Happy Hour meeting is 50 minutes long. Bring your computational questions (they do not have to be strictly related to the topic of the week) or just your curiosity. Examples and hands-on components…
Find out more »Graphing Interactions Using the PROCESS Macro in SPSS
This workshop will demonstrate how to include moderation terms (AKA interaction terms) in linear models, how to interpret the coefficients, and how to graph the interaction using the PROCESS macro in SPSS. Examples will include categorical by categorical, categorical by continuous, and continuous by continuous interactions. Any questions about this workshop can be emailed to crwells@ucla.edu. Register here: https://ucla.zoom.us/meeting/register/tJUuce-spj4rGNcYvc7hKAQPS28yTTpR14Bg
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