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Apr 17, 1:00-2:30 PM (PDT)
Chris Reidy
Location: Zoom
Get a brief overview of machine learning, see the implementation of RStudio on HPC, and participate in hands-on exercises
beginner
, high performance computing
, R
, machine learning
There will be hands-on exercises that do not assume more than basic knowledge of RStudio. It would be helpful to already ‘install.packages(“VIM”)’
Gain some take way knowledge of concepts of machine learning and reusable exercises.
Apr 18, 3-3.30 PM (PDT)
Morgan Vigil-Hayes
Location: Zoom
Learn about research infrastructure for distributed sensing and computing over sparse dnvironments through the DISCOVER Research Infrastructure project hosted at NAU.
The DISCOVER cyberinfrastructure, funded through the NSF CISE Community Research Infrastructure Program, allows researchers to study how Internet of things (IoT) devices and networks can be designed to work in technically challenging rural or remote areas.
speaker
, infrastructure
Morgan Vigil-Hayes is an assistant professor of computer science in the School of Informatics, Computing, and Cyber Systems at NAU.
Her research focuses on human-centered aspects of computer networking with the goal of innovating networked architectures, services, and policies for underserved communities.
She is a Co-PI on the DISCOVER CCRI Project.
Apr 17, 3:30-5:00 PM (PDT)
Anuj Gupta
Location: Zoom
Text mining is a valuable tool for researchers in the humanities and social sciences. By using computer languages, like Python, to analyze large textual datasets, researchers can discover new patterns and insights that were previously hidden.
This virtual workshop is designed for advanced undergraduate and graduate students who want to learn how to use text mining tools for their research. The workshop will cover a range of techniques, including distant reading, close reading, and data visualization.
beginner
, python
, text
No prior experience with programming or mining is necessary. Participants will need a computer, good internet connection and familiarity with using Zoom.
By completing this workshop, you will:
Goal 1: EXPLORE iconic studies in Humanities and Social Sciences that have used text mining techniques
Goal 2: PRACTICE how to use computational methods using Python that can help in anlaysing textual data using distant reading (frequency distributions, dispersions) and close-reading (collocations, concordances) methods.
Goal 3: BRAINSTORM how some of those techniques could be applied to your own work
https://crow.corporaproject.org/
https://dataverse.harvard.edu/dataverse/gwu-libraries
Apr 18, 9:00-10:00 AM (PDT)
Rongbo Jin
Location: Zoom
This workshop will cover basic comcepts and steps in text analysis for social scientists in R
.
beginner
, R
, text
Learners will leave with an understanding of:
R
Apr 18, 10:00 AM -12:00 PM (PDT)
Eric Scott
Location: Zoom
intermediate
, R
, packages
In this workshop, build a functional, installable R
package and learn the fundamentals of what is involved in taking your package to the next level by submitting it to a repository like CRAN.
For this workshop you'll need:
R
and using RStudioLearners will:
Apr 18, 1:00-3:00 PM (PDT)
Ivan Gonzalez
Location: NAU - Du Bois South Union, Juniper room
intermediate
, R
Hi all! We need to install the programs and libraries in the following order: QGIS (OSGeo4W), R, Rtools, Rstudio and R libraries.
This will take a long, so please consider to install them a day before
Here the folder with the executables: https://drive.google.com/drive/folders/1CLhh_Quiwt78hDk2b5AUW7ezkZhgp3Nk?usp=share_link
Apr 18, 3:00-4:00 PM (PDT)
Gil Speyer
Location: ASU - Goldwater Center for Science and Engineering, room 487
intermediate
, graphics processing
GPUs can potentially offer order-of-magnitude scaling, but it is important to understand the kinds of computations that lend themselves to this.
This session will survey the various methods of exploiting GPU in computing.
It will be helpful for learners to have an understanding of programming concepts (no specific language)
Learners will improve their general understanding of GPU.
Apr 18, 4:00-5:00 PM (PDT)
Gil Speyer
location: ASU - Goldwater Center for Science and Engineering, room 487
intermediate
, graphics processing
, high performance computing
This workshop will focus on approaches to porting MATLAB applications to a larger scale or accelerated compute resource such as a supercomputer or a GPU.
This is not an introduction to MATLAB course - learners should have a general understanding of Matlab programming
jfdkls
Learners will gain a better understanding of computational possibilities with Matlab.
Apr 18, 6:00 PM -8:00 PM (PDT)
Tucson Python Meetup community
Location: UArizona Libraries CATalyst Studio, room 254
Zoom link: https://roche.zoom.us/j/92517258720
Passcode: 632128
python
, social
Tucson Python Meetup @ ResBaz AZ: Poppy Argus talks about "Web in Python with Flask"
Apr 19, 9:00-10:00 AM (PDT)
Fernando Rios, PhD
Location: Zoom
beginner
, data publishing
How do you publish data to make it findable and reusable?
Learn how to curate and prepare your data for publication in data repositories like ReDATA.
Fernando Rios is situated within the Libraries and provides data management and curation services for UA researchers.
His academic background is in physics, geography, and computational hydrogeology.
Slides: https://osf.io/d8kfh
Apr 19, 10:00 AM -12:00 PM (PDT)
MD Nafis Ul Alam
Location: UArizona Libraries CATalyst Studio, Zoom
beginner
, intermediate
, statistics
, R
We will begin with basic concepts in probability theory such as random variables, expectation values and probability distributions.
We will then look at some properties of commonly used distributions like the Binomial, Poisson, Normal and Gamma. We will inspect the central limit theorem and observe how statistical tests compute p-values.
We will end with conditional probabilities and the basics of Bayesian estimation. We will practice some intuitive methods for parameter estimation using maximum likelihood and Markov Chain Monte Carlo.
Slides: https://tinyurl.com/RezBaz23slides
Code: https://tinyurl.com/RezBaz23code
As we cover theory and concepts, we will follow along with examples and exercises in RStudio. Prior knowledge of R is not a prerequisite, but it will be helpful to have RStudio installed on your computer so you can execute the provided scripts, play around with the code and try solving practice problems.
Learners will:
Section 1: Fundamental concepts
Section 2: Applications of probability distributions
Distribution functions in R
dfunc; pfunc; qfunc(qfunc); rfunc(simulating random variables)
Discrete distributions: Binomial and Poisson
Discrete distribution
Binomial
Poisson: expectation = variance =
Bimomial converges to poisson when rates goes below 1, we can treat it as probability; For poisson there is no upper/lower bounds.
Countinuous distribution
Normal distribution
The central limit theorem and standard error of the mean
Continuous distributions: Normal, Gamma, Chi2, T, F
Gamma: a factorial for a fractions;
Sum of squares: how spread the data are; model comparison
T test: whether a particular mean is siginificant from the population mean
F test:
Section 3: Parameter estimation
Prelude to simulations: the three-door problem
Conditional probabilities and Bayes’ theorem
Maximum likelihood estimation
Monte Carlo estimations and MCMC sampling
Apr 19, 1:00-2:00 PM (PDT)
Ken Youens-Clark
Location: Zoom
beginner
, python
TBA
Apr 19, 2:00-3:00 PM (PDT)
Devin Bayly
Location: Zoom
beginner
, 3D animation
This workshop will be an introduction to using blender in the domain of scientific visualization.
We will cover bringing in csv data and how we can associate it with geometry that we render for high quality visualizations.
Open to all learners!
–> Please Download Blender ahead of time https://www.blender.org/download/
–> Then go get the release files here https://github.com/DevinBayly/blender_CSV_resbaz
Please make sure to install the latest blender program (3.5) @ https://www.blender.org/download/
Participants will become familiar with blender in the following ways:
Apr 20, 8:30 AM - 5:00 PM (PDT)
UArizona Student Union Kachina Room
data science
, speaker sessions
Women in Data Science (WiDS) Tucson is an independent event organized by the University of Arizona to coincide with the Global WiDS Conference held at Stanford University and an estimated 200+ locations worldwide annually.
Apr 20, 4:00 PM -7:00 PM (PDT)
Snakes and Lattes Tempe, 20 West 6th St, Tempe, AZ
Mother Road Brewing Company, 7 S Mikes Pike St, Flagstaff, AZ
Snakes & Lattes, 988 E University Blvd, Tucson, AZ
social
Celebrate the end of ResBaz AZ 2023!