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X-ORIGINAL-URL:https://micde.umich.edu
X-WR-CALDESC:Events for Michigan Institute for Computational Discovery and Engineering
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TZID:America/Detroit
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DTSTART:20190310T070000
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200303T100000
DTEND;TZID=America/Detroit:20200303T140000
DTSTAMP:20260607T105010
CREATED:20230905T171341Z
LAST-MODIFIED:20230905T171341Z
UID:10000316-1583229600-1583244000@micde.umich.edu
SUMMARY:Introduction to Python's NumPy library
DESCRIPTION:This workshop will introduce you to the NumPy library in Python\, which is useful in scientific computing. We will cover NumPy’s n-dimensional array object and associated functions in depth\, along with related linear algebra and random number capabilities. Some familiarity with Python is expected. Computers will be available to complete exercises.
URL:https://micde.umich.edu/event/introduction-to-pythons-numpy-library/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200305T140000
DTEND;TZID=America/Detroit:20200305T170000
DTSTAMP:20260607T105010
CREATED:20230905T171341Z
LAST-MODIFIED:20230905T171341Z
UID:10000350-1583416800-1583427600@micde.umich.edu
SUMMARY:Visualization of spatial data
DESCRIPTION:This workshop will cover basic concepts and tools available in QGIS and R for visualizing spatial data. We will cover vector data but will also touch upon the visualization of raster and spatial network data. \nParticipants should have some familiarity with R\, but exposure to QGIS is not required.
URL:https://micde.umich.edu/event/visualization-of-spatial-data/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200306T143000
DTEND;TZID=America/Detroit:20200306T160000
DTSTAMP:20260607T105010
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000323-1583505000-1583510400@micde.umich.edu
SUMMARY:R by Example: Functional Programming with data.table
DESCRIPTION:In the R by Example series of workshops\, we’ll discuss example analyses in R as a vehicle for learning  commonly used tools and programming patterns. The “Functional Programming with dplyr” workshop will initially focus on analyzing winter home temperatures in the US using data from the Residential Energy Consumption Survey (https://www.eia.gov/consumption/residential/).  We’ll use the data.table package for data manipulation\, and then demonstrate how to encapsulate the basic pattern within a function. Such functional programming allows us to repeatedly apply this pattern to answer other questions about this data. By using a function\, we make our code more concise and easier to understand. This workshop is geared towards intermediate to advanced R users\, or as a follow-up to the “Analyzing RECS using data.table” workshop.
URL:https://micde.umich.edu/event/r-by-example-functional-programming-with-data-table/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200309T150000
DTEND;TZID=America/Detroit:20200309T170000
DTSTAMP:20260607T105010
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000337-1583766000-1583773200@micde.umich.edu
SUMMARY:Survival analysis in Python
DESCRIPTION:Survival analysis is used when working with data that may be censored\, as often is the case in studies of human subjects with incomplete follow-up.  The presence of censoring makes most forms of regression and other standard statistical analyses inappropriate. A body of specialized techniques for analyzing this type of data has been developed\, including methods for estimating and comparing marginal survival functions\, and regression methods including the widely-utilized Cox proportional hazards model.  This workshop will briefly review the key principles of survival analysis\, then illustrate by example how various survival analysis methods can be carried out using Python with the Statsmodels package.  \nParticipants should bring a laptop if they want to work with the examples during the presentation\, but this is optional.
URL:https://micde.umich.edu/event/survival-analysis-in-python-3/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200310T083000
DTEND;TZID=America/Detroit:20200310T153000
DTSTAMP:20260607T105010
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000328-1583829000-1583854200@micde.umich.edu
SUMMARY:Introduction to SAS: Simple Inference Procedures
DESCRIPTION:Prerequisites: Participant should have some familiarity with introductory statistics and be able to load data into and perform basic data manipulations in SAS. \nIn this one-day\, six-hour workshop we will discuss the basics of using SAS for statistical inference and modeling. The workshop is held in a computer lab and will alternate between instructor presentations and attendee work sessions.  After this course the attendee will be able to perform\, in SAS\, basic statistical inference procedures (hypothesis tests\, confidence intervals) for a variety of data scenarios such as one-sample\, independent-samples\, and paired-sample t-tests; chi-square test of independence of two categorical variables;  correlation between two interval variables; ANOVA; simple and multiple linear regression; and simple and multiple logistic regression. Good statistical practice will be demonstrated but this workshop is not designed to teach statistics.
URL:https://micde.umich.edu/event/introduction-to-sas-simple-inference-procedures/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200313T140000
DTEND;TZID=America/Detroit:20200313T163000
DTSTAMP:20260607T105010
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000349-1584108000-1584117000@micde.umich.edu
SUMMARY:Regular Expressions
DESCRIPTION:Regular expressions are perfectly suited for people who like puzzles. Regular expressions are a sequence of characters used to define a search pattern. They are commonly used to do “find” and “find and replace” string operations. They are also used to validate strings like phone numbers\, passwords\, etc. in data entry. Regular expression capabilities can be found in a variety of programming languages and software like ArcGIS\, Java\, Javascript\, Matlab\, Perl\, PHP\, Python\, R\, Visual Basic\, etc. and some text editors. \nThe workshop will consist of hands-on example problems. Learn to search beyond “*.txt”. The tutorials will be conducted using Python. A basic programming background is helpful but not required for this workshop.
URL:https://micde.umich.edu/event/regular-expressions-4/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200316T150000
DTEND;TZID=America/Detroit:20200316T170000
DTSTAMP:20260607T105010
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000338-1584370800-1584378000@micde.umich.edu
SUMMARY:Go for data processing Part 1
DESCRIPTION:This is a two-session workshop on the use of Go for data processing.  Go is an open source language developed for general-purpose programming.  It is not more difficult to learn and use than a high-level scripting language like Python\, but it is strongly typed\, statically compiled\, and provides native support for concurrency\, leading to much better performance for many common tasks.  In this series of workshops\, we introduce Go as a tool for data processing. No prior exposure to Go is expected\, but participants should have some programming background. Free and open source tools for Go are available for all common platforms.   \nParticipants should bring a laptop if they want to work with the examples during the presentation\, but this is optional.
URL:https://micde.umich.edu/event/go-for-data-processing-part-1/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200319T140000
DTEND;TZID=America/Detroit:20200319T160000
DTSTAMP:20260607T105010
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000324-1584626400-1584633600@micde.umich.edu
SUMMARY:Machine Learning in R
DESCRIPTION:In this workshop\, we’ll first discuss core machine learning concepts such as: choosing loss functions and evaluation metrics; splitting the data into training\, validation\, and testing sets; and cross-validation patterns for tuning hyper-parameters. Next\, we’ll apply these concepts to train models for identifying isolated letters from speech (https://archive.ics.uci.edu/ml/datasets/isolet). \nSpecifically\, we’ll apply the elastic net (a generalization of ridge and lasso regression)\, random forests\, and gradient boosting to this task.  We’ll briefly discuss each model/method but our primary focus will be on understanding the core functionality of the related R packages (glmnet\, randomForests\, xgboost) and tuning associated hyper-parameters.
URL:https://micde.umich.edu/event/machine-learning-in-r/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200323T150000
DTEND;TZID=America/Detroit:20200323T170000
DTSTAMP:20260607T105010
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000339-1584975600-1584982800@micde.umich.edu
SUMMARY:Go for data processing Part 2
DESCRIPTION:This is a two-session workshop on the use of Go for data processing.  Go is an open source language developed for general-purpose programming.  It is not more difficult to learn and use than a high-level scripting language like Python\, but it is strongly typed\, statically compiled\, and provides native support for concurrency\, leading to much better performance for many common tasks.  In this series of workshops\, we introduce Go as a tool for data processing. No prior exposure to Go is expected\, but participants should have some programming background. Free and open source tools for Go are available for all common platforms.   \nParticipants should bring a laptop if they want to work with the examples during the presentation\, but this is optional.
URL:https://micde.umich.edu/event/go-for-data-processing-part-2/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200324T100000
DTEND;TZID=America/Detroit:20200324T120000
DTSTAMP:20260607T105010
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000317-1585044000-1585051200@micde.umich.edu
SUMMARY:Introduction to Deep Neural Networks with Keras/TensorFlow
DESCRIPTION:Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level\, Python interface running on top of multiple neural network libraries\, including the popular library TensorFlow. In this workshop\, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification with standard fully-connected DNNs\, as well as image classification using Convolutional Neural Networks (CNNs). We will also look at regularization techniques and how to deal with under- and over-fitting. All examples will use Python; some familiarity with Python is recommended. Computers will be available to complete exercises. We will run the models using Google Colab\, which requires a Google account.
URL:https://micde.umich.edu/event/3601/
CATEGORIES:Workshops
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200325T100000
DTEND;TZID=America/Detroit:20200325T120000
DTSTAMP:20260607T105010
CREATED:20230905T171343Z
LAST-MODIFIED:20230905T171343Z
UID:10000344-1585130400-1585137600@micde.umich.edu
SUMMARY:Building software projects: CMake is more than a build tool
DESCRIPTION:This workshop is a continuation of the previous workshop “Building software projects: use CMake to build the building plan”.  In this workshop\, we will see that CMake is not just a fancy Makefile generator: it can help us to test\, reuse\, and distribute our software!  We will use CMake to build two interdependent multi-language projects\, and demonstrate how to invoke unit tests after the build\, how to make our code discoverable and reusable by other software developers\, and how to create a distributable package.  If you intend to distribute your software to other research groups\, or if you expect that your project will grow beyond a few files of code and a few months of use — this workshop is for you! \nParticipants will need to have laptops with WiFi connection if they wish to follow the hands-on exercises.  A basic knowledge of Unix-like operating systems would be helpful in following and understanding the material\, but is not required.
URL:https://micde.umich.edu/event/building-software-projects-cmake-is-more-than-a-build-tool/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
GEO:42.2807892;-83.7381556
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Rackham Building Earl Lewis Room 3rd Floor East 915 E. Washington St. Ann Arbor MI 48109 United States;X-APPLE-RADIUS=500;X-TITLE=915 E. Washington St.:geo:-83.7381556,42.2807892
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20200330T130000
DTEND;TZID=America/Detroit:20200330T160000
DTSTAMP:20260607T105010
CREATED:20230905T171342Z
LAST-MODIFIED:20230905T171342Z
UID:10000303-1585573200-1585584000@micde.umich.edu
SUMMARY:Data Visualization With 3D Graphics Using Unity3D and C#
DESCRIPTION:This session will be held online\, and presenters will be in touch with more information after you register. \n  \nVideo game development is more accessible than ever before thanks to modern software tools\, with many options free to download. These tools are also used to program more “serious” applications that require interactive 3D graphics\, from mobile apps\, virtual and augmented reality\, computer vision and artificial intelligence\, and real-time CGI film production.  \n  \nUnity3D is a powerful and popular game engine for both hobbyist and professional projects\, able to compile a ‘game’ to almost any computer platform\, and free to download for non-commercial use. This workshop will show how you can use it to render data from research projects in a 3D interactive representation for user analysis and demonstration. \n  \nIn this workshop\, we introduce the Unity3D workspace\, and prepare a demo that allows the user to load an example dataset and view it as a simple set of 3D representations. A basic familiarity with any computer programming language (C# will be used during the session) is recommended to get the most out of the workshop. To take part\, users will be responsible to bring their own laptop with Unity3D (available for Windows\, Macintosh and Linux) pre-installed. Additional project files will be provided to registered users ahead of the workshop date.
URL:https://micde.umich.edu/event/data-visualization-with-3d-graphics-using-unity3d-and-c-2/
LOCATION:Your Desktop
CATEGORIES:Workshops
END:VEVENT
END:VCALENDAR