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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181025T100000
DTEND;TZID=America/Los_Angeles:20181025T120000
DTSTAMP:20260619T211041
CREATED:20180913T233330Z
LAST-MODIFIED:20181004T175831Z
UID:11289-1540461600-1540468800@idre.ucla.edu
SUMMARY:Introduction to Jupyter
DESCRIPTION:RSVP FOR EVENT\nThe Jupyter Notebook is a computing tool that allows users to edit and run Python\, R\, Julia (and many other programming languages) inside a web browser. Furthermore\, it is a powerful tool that allows users to combine live code\, text\, and visualizations in an interactive\, shareable\, reproducible document. It has been growing in popularity in many scientific and research disciplines as a data exploration and analysis tool that encourages collaboration and reproducible science. This class will provide an interactive demonstration showing what the Jupyter Notebook is\, how to use it\, and how it is being used in many different fields.
URL:https://idre.ucla.edu/calendar-event/introduction-to-jupyter
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181023T100000
DTEND;TZID=America/Los_Angeles:20181023T110000
DTSTAMP:20260619T211041
CREATED:20180925T182109Z
LAST-MODIFIED:20181008T200930Z
UID:11379-1540288800-1540292400@idre.ucla.edu
SUMMARY:Informal Discussions on Machine Learning
DESCRIPTION:This is a recurring weekly event from Tuesday\, Oct. 9th – Tuesday\, Oct. 30th  (4 courses total). Please attend all weeks if your time permits. No RSVP is necessary. \nThis will be a continuation of machine learning techniques that we have been presenting through September. During the October presentations\, we will go through logistic regression\, binary classification\, multi-class classification\, neural networks\, hidden Layers\, forward propagation\, backward propagation\, L1 and L2 regularization\, sigmoid functions\, confusion matrix\,  one-hot-encoding\, softmax etc.
URL:https://idre.ucla.edu/calendar-event/deep-learning-series-3
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181023T090000
DTEND;TZID=America/Los_Angeles:20181023T120000
DTSTAMP:20260619T211041
CREATED:20180816T155310Z
LAST-MODIFIED:20181008T200941Z
UID:11021-1540285200-1540296000@idre.ucla.edu
SUMMARY:Introduction to R
DESCRIPTION:RSVP FOR EVENT\nR is statistical package that runs on Windows\, Macintosh and UNIX platforms. This class is designed for people who are just starting to use R. The students in the class will have a hands-on experience using R for doing statistics\, graphics\, and data management. The class notes are the scripts for the class. The R class notes do not contain any of the computer output. The class notes are not meant to be an R textbook or a reference manual. The notes for the workshop can be found at: https://stats.idre.ucla.edu/r/seminars/intro/ \nNote:  All researchers are welcome to attend this workshop. However\, there will be NO online component. Please sign up only if you can attend in person.
URL:https://idre.ucla.edu/calendar-event/introduction-to-r-6
LOCATION:CLICC Classroom C\, 320 Powell Library\, 10740 Dickson Court\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181022T140000
DTEND;TZID=America/Los_Angeles:20181022T160000
DTSTAMP:20260619T211041
CREATED:20180913T233028Z
LAST-MODIFIED:20181004T183317Z
UID:11286-1540216800-1540224000@idre.ucla.edu
SUMMARY:Introduction to Message Passing Interface (MPI)
DESCRIPTION:RSVP FOR EVENT\nMPI (message passing interface) is the de facto standard for distributed-memory parallel scientific computing. While the entire MPI API is quite extensive\, this class will cover a number of key ingredients commonly used in practice. This class is useful for those who plan to start writing MPI code\, and for those who would like to know how MPI works in order to operate an existing MPI code. Working knowledge of C and Fortran programming languages will be very helpful to follow the class materials. \nSpecifically\, we will discuss: \n\nMPI basics\nOne-to-one communication examples\nCollective communication examples\nRunning MPI programs
URL:https://idre.ucla.edu/calendar-event/introduction-to-message-passing-interface-mpi
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181019T140000
DTEND;TZID=America/Los_Angeles:20181019T160000
DTSTAMP:20260619T211041
CREATED:20180913T232131Z
LAST-MODIFIED:20181004T190820Z
UID:11282-1539957600-1539964800@idre.ucla.edu
SUMMARY:Python for High Performance Computing
DESCRIPTION:RSVP FOR EVENT\nPython\, originally developed as a general-purpose programming language\, has gained its popularity in the scientific community in recent years owing to its elegant and easy-to-understand syntax and powerful libraries. Python fully supports both functional and object-oriented programming styles. This class will discuss a number useful features of Python in the context of scientific computing\, and introduce a number of supporting packages\, including numpy for fast array-based computations\, h5py to access HDF5 files\, and the use of Python in MPI-style parallel computing.
URL:https://idre.ucla.edu/calendar-event/python-for-high-performance-computing
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181019T100000
DTEND;TZID=America/Los_Angeles:20181019T120000
DTSTAMP:20260619T211041
CREATED:20180913T231822Z
LAST-MODIFIED:20181008T201256Z
UID:11279-1539943200-1539950400@idre.ucla.edu
SUMMARY:Introduction to Science Gateway
DESCRIPTION:RSVP FOR EVENT\n“Science Gateway” refers to a web or mobile-based applications with user-friendly interfaces enabling access to advanced technology resources to support scientific research and/or education. This 2-hour session aims to provide fundamental information about Science Gateway technologies. Three covered topics include: \n\nWhat Science Gateways really refer to and what Science Gateways can provide to researchers and educators.\nThe efforts from UCLA IDRE for implementing a Science Gateway.\nThe visions and planning of UCLA Science Gateway provided from IDRE.\n\nNo prerequisites\, but we recommend that you take the UCLA IDRE Science Gateway Survey before or after the session.
URL:https://idre.ucla.edu/calendar-event/introduction-to-science-gateway
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20181017
DTEND;VALUE=DATE:20181019
DTSTAMP:20260619T211041
CREATED:20180906T183135Z
LAST-MODIFIED:20181008T201354Z
UID:11211-1539734400-1539907199@idre.ucla.edu
SUMMARY:SAS SQL 1: Essentials
DESCRIPTION:RSVP FOR THE EVENT\n2-Day Workshop\, 9am – 5pm Daily\nThis course teaches you how to process SAS data using Structured Query Language (SQL). Learn how to query and subset data\, summarize and present data\, combine tables\, including complex joins and merges\, create and modify table views and indexes\, replace multiple DATA and PROC steps with one SQL query. This course can help prepare you for the following certification exam(s): SAS Advanced Programming for SAS 9. \nBefore attending this class\, you should be able to: \n\nSubmit SAS programs on your operating system\nCreate and access SAS data sets\nUse arithmetic\, comparison\, and logical operators\nInvoke SAS procedures\n\nYou can gain this experience from the SAS Programming 1 course. No knowledge of SQL is necessary. \nNote: This is event is open to only those currently affiliated with the University of California. \n\nFor registration and more information\, please visit the IDRE Stats Seminars page.
URL:https://idre.ucla.edu/calendar-event/sas-sql-1-essentials
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181016T100000
DTEND;TZID=America/Los_Angeles:20181016T110000
DTSTAMP:20260619T211041
CREATED:20180925T181005Z
LAST-MODIFIED:20181008T201029Z
UID:11377-1539684000-1539687600@idre.ucla.edu
SUMMARY:Informal Discussions on Machine Learning
DESCRIPTION:This is a recurring weekly event from Tuesday\, Oct. 9th – Tuesday\, Oct. 30th  (4 courses total). Please attend all weeks if your time permits. No RSVP is necessary. \nThis will be a continuation of machine learning techniques that we have been presenting through September. During the October presentations\, we will go through logistic regression\, binary classification\, multi-class classification\, neural networks\, hidden Layers\, forward propagation\, backward propagation\, L1 and L2 regularization\, sigmoid functions\, confusion matrix\,  one-hot-encoding\, softmax etc.
URL:https://idre.ucla.edu/calendar-event/deep-learning-series-2
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20181015
DTEND;VALUE=DATE:20181017
DTSTAMP:20260619T211041
CREATED:20180906T170303Z
LAST-MODIFIED:20181008T201117Z
UID:11197-1539561600-1539734399@idre.ucla.edu
SUMMARY:SAS Macro Language 1: Essentials
DESCRIPTION:RSVP FOR THE EVENT\n2-Day workshop\, 9:00am – 5:00pm daily\nThis course focuses on the components of the SAS macro facility and how to design\, write\, and debug macro systems. Emphasis is placed on understanding how programs with macro code are processed. Learn how to perform text substitution in SAS code\, automate and customize the production of SAS code\, conditionally or iteratively construct SAS code and use macro variables and macro functions. This course can help prepare you for the following certification exams: SAS Advanced Programming for SAS 9\, SAS Certified Clinical Trials Programmer Using SAS 9. \nBefore attending this course\, you should have either completed the SAS Programming 2: Data Manipulation Techniques course or have equivalent knowledge. Specifically\, you should be able to: \n\nUse a DATA step to read from or write to a SAS data set or external file\nUse DATA step programming statements such as IF-THEN/ELSE\, DO WHILE\, DO UNTIL\, and iterative DO\nUse SAS data set options such as DROP=\, KEEP=\, and OBS=\nUse character functions such as SUBSTR\, SCAN\, INDEX\, and UPCASE\nForm subsets of data using the WHERE clause\nCreate and use SAS date values and constants\nUse SAS procedures such as SORT\, PRINT\, CONTENTS\, MEANS\, FREQ\, TABULATE\, and CHART.\n\nNote: This event is open to current University of California affiliates. \n\nFor registration and more information\, please visit the IDRE Stats Seminars page.
URL:https://idre.ucla.edu/calendar-event/sas-macro-language-1-essentials
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181010T130000
DTEND;TZID=America/Los_Angeles:20181010T150000
DTSTAMP:20260619T211041
CREATED:20180918T163717Z
LAST-MODIFIED:20180924T162049Z
UID:11303-1539176400-1539183600@idre.ucla.edu
SUMMARY:Introducing Python for Data Science and the Web
DESCRIPTION:RSVP FOR THE EVENT \nThis entry-level workshop will introduce Python as a tool for digital researchers and scholars wanting to incorporate data on the web. The following Python libraries will be covered: requests\, lxml\, pandas\, and numpy. \nFind other UCLA Library\, Advanced Research Workshop Series
URL:https://idre.ucla.edu/calendar-event/introducing-python-for-data-science-and-the-web
LOCATION:West Electronic Classroom\, 23167 Young Research Library\, 280 Charles E Young Drive North\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181009T100000
DTEND;TZID=America/Los_Angeles:20181009T110000
DTSTAMP:20260619T211041
CREATED:20180925T164435Z
LAST-MODIFIED:20181008T201148Z
UID:11375-1539079200-1539082800@idre.ucla.edu
SUMMARY:Informal Discussions on Machine Learning
DESCRIPTION:This is a recurring weekly event from Tuesday\, Oct. 9th – Tuesday\, Oct. 30th  (4 courses total). Please attend all weeks if your time permits. No RSVP is necessary. \nThis will be a continuation of machine learning techniques that we have been presenting through September. During the October presentations\, we will go through logistic regression\, binary classification\, multi-class classification\, neural networks\, hidden Layers\, forward propagation\, backward propagation\, L1 and L2 regularization\, sigmoid functions\, confusion matrix\,  one-hot-encoding\, softmax etc.
URL:https://idre.ucla.edu/calendar-event/deep-learning-series
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181009T090000
DTEND;TZID=America/Los_Angeles:20181009T120000
DTSTAMP:20260619T211041
CREATED:20180816T154057Z
LAST-MODIFIED:20181004T191042Z
UID:11019-1539075600-1539086400@idre.ucla.edu
SUMMARY:Introduction to SAS
DESCRIPTION:RSVP FOR EVENT\nSAS is a powerful statistical package that runs on many platforms\, including Windows and Unix. This class is designed for people who are just getting started using SAS. The students in the class will have a hands-on experience using SAS for statistics\, graphics\, and data management. The SAS class notes do not contain any of the computer output. The class notes are not meant to be a SAS textbook or a reference manual. The notes for the workshop can be found at: https://stats.idre.ucla.edu/sas/seminars/notes/ \nNote: All researchers are welcome to attend this workshop. However\, there will be NO online component. Please sign up only if you can attend in person.
URL:https://idre.ucla.edu/calendar-event/introduction-to-sas-3
LOCATION:CLICC Classroom C\, 320 Powell Library\, 10740 Dickson Court\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181008T140000
DTEND;TZID=America/Los_Angeles:20181008T160000
DTSTAMP:20260619T211041
CREATED:20180913T233449Z
LAST-MODIFIED:20181008T201543Z
UID:11292-1539007200-1539014400@idre.ucla.edu
SUMMARY:Running Applications on the Hoffman2 Cluster: Case Studies
DESCRIPTION:RSVP FOR EVENT\n\nThis class will address the process of creating Matlab standalone executables and running Matlab in batch\, as well as running Abaqus python scripts. Example of how to submit array jobs using Abaqus\, R and other applications. Can my simulations be submitted as array jobs? Bring your own problem. Also\, Jupyter Notebooks: another way to run python and R on Hoffman2.
URL:https://idre.ucla.edu/calendar-event/running-applications-on-the-hoffman2-cluster-case-studies
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181003T130000
DTEND;TZID=America/Los_Angeles:20181003T150000
DTSTAMP:20260619T211041
CREATED:20180918T163734Z
LAST-MODIFIED:20180920T225225Z
UID:11306-1538571600-1538578800@idre.ucla.edu
SUMMARY:Introduction to GIS: Got Data? Map it!
DESCRIPTION:RSVP FOR THE EVENT\nIt is said that more than 80% of all data has a spatial component to it. As more and more research is leaning towards spatial analysis\, this course offers an introduction to Geographic Information Systems\, GIS\, as a means to spatialize and analyze your data. As a hands-on course\, you will learn how to download data\, manipulate and join data to existing geographic boundaries\, and create stunning cartographic representations. There are no pre-requisite requirements to take this workshop. \nFind other UCLA Library\, Advanced Research Workshop Series
URL:https://idre.ucla.edu/calendar-event/introduction-to-gis-got-data-map-it
LOCATION:West Electronic Classroom\, 23167 Young Research Library\, 280 Charles E Young Drive North\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181002T100000
DTEND;TZID=America/Los_Angeles:20181002T110000
DTSTAMP:20260619T211041
CREATED:20180830T182150Z
LAST-MODIFIED:20180913T203354Z
UID:11181-1538474400-1538478000@idre.ucla.edu
SUMMARY:Google Machine Learning Crash Course
DESCRIPTION:This is a recurring weekly event from Tuesday\, Sept. 4th – Tuesday\, Oct. 2nd (5 courses total). Please attend all weeks if your time permits. No RSVP is necessary. \nFor the past several weeks we have presented data frames in Python\, R and Julia. Now that we are all familiar with Python Pandas data frame\, we will start applying our knowledge to Machine learning. To guide us through the process we will use the course notes and exercises provided at the Google Machine Learning Crash Course site. \n\n10/2/18 Course details coming soon…
URL:https://idre.ucla.edu/calendar-event/google-machine-learning-crash-course-5
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181002T090000
DTEND;TZID=America/Los_Angeles:20181002T120000
DTSTAMP:20260619T211041
CREATED:20180816T153321Z
LAST-MODIFIED:20181219T200806Z
UID:11016-1538470800-1538481600@idre.ucla.edu
SUMMARY:Introduction to Stata
DESCRIPTION:Stata is a powerful and yet easy-to-use statistical package that runs on Windows\, Macintosh and Unix platforms. This class is designed for people who are just getting started using Stata. The students in the class will have a hands-on experience using Stata for statistics\, graphics and data management. The class notes are the scripts for the class available to the students in the class and to others on the Internet. The Stata class notes do not contain any of the output. The class notes are not meant to be a Stata textbook or a reference manual. The notes for the workshop can be found at: https://stats.idre.ucla.edu/stata/seminars/notes15/ \nNote:  All researchers are welcome to attend this workshop. However\, there will be NO online component. Please sign up only if you can attend in person.
URL:https://idre.ucla.edu/calendar-event/introduction-to-stata-4
LOCATION:CLICC Classroom C\, 320 Powell Library\, 10740 Dickson Court\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20181001T140000
DTEND;TZID=America/Los_Angeles:20181001T160000
DTSTAMP:20260619T211041
CREATED:20180913T233710Z
LAST-MODIFIED:20180920T221200Z
UID:11295-1538402400-1538409600@idre.ucla.edu
SUMMARY:Running Applications on the Hoffman2 Cluster: Introduction
DESCRIPTION:The Hoffman2 cluster is a powerful computational resource for the UCLA research community. This class is designed to clarify the process of porting your own applications on the cluster or using applications already available on the cluster. It also addresses how to port your workflow to the Hoffman2 and how to submit batch and run interactive applications.
URL:https://idre.ucla.edu/calendar-event/running-applications-on-the-hoffman2-cluster-introduction
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180925T100000
DTEND;TZID=America/Los_Angeles:20180925T110000
DTSTAMP:20260619T211041
CREATED:20180830T182105Z
LAST-MODIFIED:20180919T215333Z
UID:11179-1537869600-1537873200@idre.ucla.edu
SUMMARY:Google Machine Learning Crash Course
DESCRIPTION:This is a recurring weekly event from Tuesday\, Sept. 4th – Tuesday\, Oct. 2nd (5 courses total). Please attend all weeks if your time permits. No RSVP is necessary. \nFor the past several weeks we have presented data frames in Python\, R and Julia. Now that we are all familiar with Python Pandas data frame\, we will start applying our knowledge to Machine learning. To guide us through the process we will use the course notes and exercises provided at the Google Machine Learning Crash Course site. \n\n\n9/25/18 Course Title: “Live Demo of Machine Learning using  Amazon AWS Machine Learning Framework Interfaces”\nDuring the September 25th presentation of machine learning interfaces\, we will deploy a machine learning exercise on Amazon AWS using Amazon AWS machine learning framework interfaces.
URL:https://idre.ucla.edu/calendar-event/google-machine-learning-crash-course-4
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180918T100000
DTEND;TZID=America/Los_Angeles:20180918T110000
DTSTAMP:20260619T211041
CREATED:20180830T182004Z
LAST-MODIFIED:20180913T202939Z
UID:11177-1537264800-1537268400@idre.ucla.edu
SUMMARY:Google Machine Learning Crash Course
DESCRIPTION:This is a recurring weekly event from Tuesday\, Sept. 4th – Tuesday\, Oct. 2nd (5 courses total). Please attend all weeks if your time permits. No RSVP is necessary. \nFor the past several weeks we have presented data frames in Python\, R and Julia. Now that we are all familiar with Python Pandas data frame\, we will start applying our knowledge to Machine learning. To guide us through the process we will use the course notes and exercises provided at the Google Machine Learning Crash Course site. \n\n9/18/18 Course details coming soon…
URL:https://idre.ucla.edu/calendar-event/google-machine-learning-crash-course-3
CATEGORIES:Classes and Workshops,Education and Training
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180917T090000
DTEND;TZID=America/Los_Angeles:20180919T170000
DTSTAMP:20260619T211041
CREATED:20180731T000422Z
LAST-MODIFIED:20180913T205627Z
UID:10931-1537174800-1537376400@idre.ucla.edu
SUMMARY:University Stats Camp: Longitudinal Structural Equation Modeling (SEM) Seminar
DESCRIPTION:A comprehensive 3-day Stats Camp seminar on Longitudinal SEM.\nThis camp is an intensive seminar consisting of lectures\, discussions and one-on-one consultations to provide participants with advanced training in SEM for the analysis of longitudinal data. \nTopics include:\n\nDesign and measurement issues in cross-sectional and longitudinal research\nTraditional panel designs\nOverview of missing data\nLatent growth curve modeling\nTesting for Mediation and Moderation\nMultilevel and multiple group SEM\nUsing Phantom Constructs\nMultiple group modeling\n\n  \nInstructor\, Todd Little\, Ph.D. & Elizabeth Grandfield. Ph.D. Candidate \n9:00am – 5:00pm Daily. \nAdvanced course. Recommended for researchers\, faculty\, graduate students and Post-Docs. \nOpen to public. Registration with UCLA email address receives 25% Off Discount. Use Discount Code: UCLASTATSCAMP \nLimited Seating Available. Register soon! \nBreakfast and Lunch included. \nFor more information\, please visit the official event page on the University Statistics Camp website. \n 
URL:https://idre.ucla.edu/calendar-event/university-stats-camp-longitudinal-structural-equation-modeling-sem-seminar
CATEGORIES:Classes and Workshops,Conferences and Seminars,Education and Training,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180917T090000
DTEND;TZID=America/Los_Angeles:20180919T170000
DTSTAMP:20260619T211041
CREATED:20180731T000007Z
LAST-MODIFIED:20180913T205646Z
UID:10935-1537174800-1537376400@idre.ucla.edu
SUMMARY:University Stats Camp: Multilevel Structural Equation Modeling with xxM Seminar
DESCRIPTION:A comprehensive 3-day Stats Camp seminar on Multilevel SEM with xxM.\nThis seminar teaches skills necessary to conduct analysis of complex multilevel data-structures from an nLevel Structural Equation Modeling perspective. \nConventional multilevel modeling and multilevel-structural equation modeling work well with ‘standard’ multilevel data. The n-Level structural equation modeling (NL-SEM) framework is intended for both conventional and non-standard data-structures. Non-standard data are indeed very common across multiple domains but rarely analyzed in a satisfactory manner. \n  \nInstructor\, Paras Mehta\, Ph.D. \n9:00am – 5:00pm Daily. \nAdvanced course. Recommended for researchers\, faculty\, graduate students and Post-Docs. \nOpen to public. Registration with UCLA email address receives 25% Off Discount. Use Discount Code: UCLASTATSCAMP \nLimited Seating Available. Register soon! \nBreakfast and Lunch included. \nFor registration and more information\, please visit the official event page on the University Statistics Camp website. \n 
URL:https://idre.ucla.edu/calendar-event/university-stats-camp-multilevel-structural-equation-modeling-with-xxm-seminar
LOCATION:OIT Conference Room 5308B\, 5308B Math Sciences Building\, 520 Portola Plaza\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Classes and Workshops,Conferences and Seminars,Education and Training,Presentations
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180911T100000
DTEND;TZID=America/Los_Angeles:20180911T110000
DTSTAMP:20260619T211041
CREATED:20180830T181856Z
LAST-MODIFIED:20180910T202130Z
UID:11175-1536660000-1536663600@idre.ucla.edu
SUMMARY:Google Machine Learning Crash Course
DESCRIPTION:This is a recurring weekly event from Tuesday\, Sept. 4th – Tuesday\, Oct. 2nd (5 courses total). Please attend all weeks if your time permits. No RSVP is necessary. \nFor the past several weeks we have presented data frames in Python\, R and Julia. Now that we are all familiar with Python Pandas data frame\, we will start applying our knowledge to Machine learning. To guide us through the process we will use the course notes and exercises provided at the Google Machine Learning Crash Course site. \n\n9/11/18 Course Title: “Machine Learning using Linear Regression in Tensorflow”\nDuring this week’s Machine Learning class we will work through examples that use Linear Regression algorithms in Tensorflow. Please attend if you are interested in learning Tensorflow APIs.
URL:https://idre.ucla.edu/calendar-event/google-machine-learning-crash-course-2
CATEGORIES:Classes and Workshops,Education and Training
ORGANIZER;CN="Prakashan Korambath":MAILTO:ppk@idre.ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180905T080000
DTEND;TZID=America/Los_Angeles:20180906T140000
DTSTAMP:20260619T211041
CREATED:20180821T223909Z
LAST-MODIFIED:20180829T234531Z
UID:11072-1536134400-1536242400@idre.ucla.edu
SUMMARY:XSEDE HPC Workshop: BIG DATA
DESCRIPTION:UCLA-IDRE along with XSEDE and Pittsburgh Supercomputing Center is pleased to announce a two day Big Data workshop (Sept 5-6\, 2018\, 8 AM-2 PM PDT each day). \nThis workshop will focus on topics such as Hadoop and Spark and will be presented using the Wide Area Classroom (WAC) training platform. \nFor registration and detailed information\, visit: https://www.psc.edu/current-workshop \nAgenda: \n\n\n\nWednesday\, September 5\, 2018\nAll times given are Pacific\n\n\n08:00\nWelcome\n\n\n08:25\nIntro to Big Data\n\n\n09:00\nHadoop\n\n\n09:30\nIntro to Spark\n\n\n10:00\nLunch Break\n\n\n11:00\nSpark\n\n\n12:30\nSpark Exercises\n\n\n01:30\nSpark\n\n\n02:00\nAdjourn\n\n\n\n  \n\n\n\nThursday\, September 6\, 2018\nAll times given are Pacific\n\n\n08:00\nMachine Learning: Recommender System with Spark\n\n\n10:00\nLunch break\n\n\n11:00\nDeep Learning with Tensorflow\n\n\n01:30\nBridges: A Big Data Platform\n\n\n02:00\nAdjourn\n\n\n\n 
URL:https://idre.ucla.edu/calendar-event/workshop-big-data-sept-2018
ORGANIZER;CN="T V Singh":MAILTO:tvsingh@ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180904T100000
DTEND;TZID=America/Los_Angeles:20180904T110000
DTSTAMP:20260619T211041
CREATED:20180829T233023Z
LAST-MODIFIED:20180830T181335Z
UID:11168-1536055200-1536058800@idre.ucla.edu
SUMMARY:Google Machine Learning Crash Course
DESCRIPTION:This is a weekly event\, starting September 4th\, Tuesday and ending October 2nd\, Tuesday. \nFor the past several weeks we have presented data frames in Python\, R and Julia. Now that we are all familiar with Python Pandas data frame\, we will start applying our knowledge to Machine learning. To guide us through the process we will use the course notes and exercises provided at the Google Machine Learning Crash Course site. Please attend all weeks if your time permits. \nNo RSVP is necessary.
URL:https://idre.ucla.edu/calendar-event/google-machine-learning-crash-course
ORGANIZER;CN="Prakashan Korambath":MAILTO:ppk@idre.ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180822T100000
DTEND;TZID=America/Los_Angeles:20180822T130000
DTSTAMP:20260619T211041
CREATED:20180730T185809Z
LAST-MODIFIED:20180821T000005Z
UID:10892-1534932000-1534942800@idre.ucla.edu
SUMMARY:Build\, Train\, and Deploy ML Models at Scale with Amazon SageMaker
DESCRIPTION:In this tutorial participants learn to solve Machine / Deep Learning problems using the tools available in the Amazon Web Services (AWS) cloud. The development and application of machine learning models is a vital part of scientific and technical computing. Increasing model training data size generally improves model prediction and performance\, but deploying models at scale is a challenge. Participants will learn to use Amazon SageMaker\, a new AWS service that simplifies the machine learning process and enables training on cloud stored datasets at any scale. \nApplications will include: \n\nsatellite imagery\, MXNet\, LandSat dataset : automatically mapping buildings in Vietnam\nchemistry\, DeepChem: building an online compound solubility prediction workflow\ngenomics\, 1000 genomes dataset\n\nThe tutorial will walk attendees through the process of building a model\, training it\, and applying it for prediction. Working in web-based Jupyter Notebooks powered by AWS\, we’ll explore common algorithms (e.g. k-means and PCA) and deep learning with MXNet and TensorFlow. Participants will become familiar with SDKs for Python and Spark and other APIs that make machine learning with AWS easy to use. With Amazon SageMaker\, users take their code and analysis to the data\, and participants will experiment on real-world datasets\, such as Earth on AWS and the Cancer Genome Atlas. At the end of the session\, attendees will have the resources and experience to start using Amazon SageMaker and other AWS services to accelerate their scientific research and time to discovery. \nFood: Pizza will be served. \n\nIntended audience \nMachine Learning Practitioners old and new: developers\, scientists\, data science practitioners\, research staff\, and any other interested persons. Participants should have some familiarity with: \n\npython\njupyter notebooks\nbasic machine learning methods\n\n\nAgenda \n10:00:  Speaker and Facilitator Introductions\n10:05:  Introduction to Amazon Sagemaker\n10:25:  Environment Setup\n10:45:  Lab 1 – Digit Classification with the Amazon Linear Learner Algorithm; guided walk-through and recap\n11:15:  Lab 2 – Distributed Training with TensorFlow (self-guided)\n11:45:  Lab 3 – How to Bring Your Own Model (self-guided)\n12:15:  Break\n12:20:  Lab 4 – Using Public Datasets (self-guided)\n12:50:  Closing and pizza \n\nPrereqs for Workshop \n\nAWS Account (already created)\nAccess to SageMaker\, S3\, ECR from your IAM role.\nAccess to SageMaker service role AmazonSageMaker-ExecutionRole or ability to create IAM roles.\n\nPlease make sure to have these taken care of prior to the workshop.  If you do not have an account\, please open an account following the directions on Software Central here:  (a $0 PO is fine if you don’t want to use a credit card.)  https://softwarecentral.ucla.edu/amazon-aws-howto.  If you have questions\, please email matsonh@amazon.com. \nNote:  AWS will provide credits so you will not incur charges related to the workshop (as long as you shut down any resources running in your account after the workshop concludes). \n\nRSVP by visiting the following link: RSVP form\n 
URL:https://idre.ucla.edu/calendar-event/build-train-and-deploy-ml-models-at-scale-with-amazon-sagemaker
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180814T100000
DTEND;TZID=America/Los_Angeles:20180814T230000
DTSTAMP:20260619T211041
CREATED:20180809T221858Z
LAST-MODIFIED:20180809T221858Z
UID:11014-1534240800-1534287600@idre.ucla.edu
SUMMARY:Data contextualization with Python Pandas Dataframe
DESCRIPTION:We will present Data Contextualization using Python Pandas dataframe on August 14th 2018 @10:00 am in room 3909 MSA.  We will also do some benchmark with Julia on the same problem. \n  \nPlease attend if your time permits.  Thanks.
URL:https://idre.ucla.edu/calendar-event/data-contextualization-with-python-pandas-dataframe
ORGANIZER;CN="Prakashan Korambath":MAILTO:ppk@idre.ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180807T100000
DTEND;TZID=America/Los_Angeles:20180807T120000
DTSTAMP:20260619T211041
CREATED:20180730T155833Z
LAST-MODIFIED:20180730T160003Z
UID:10890-1533636000-1533643200@idre.ucla.edu
SUMMARY:CESMII/UCLA Presentation: Rolling mill exit temperature prediction data contextualization workflow with Matlab and Julia on August 7th 2018 Tuesday @10:00 am in room 3909 MSA (Part II)
DESCRIPTION:  \nWe will do a demo of Kepler workflow to contextualize the data used for rolling mill exit temperature prediction.  This will be talk 2 of this series.  We will be running the workflow in 3-way parallel mode.
URL:https://idre.ucla.edu/calendar-event/cesmii-ucla-presentation-rolling-mill-exit-temperature-prediction-data-contextualization-workflow-with-matlab-and-julia-on-august-7th-2018-tuesday-1000-am-in-room-3909-msa-part-ii
ORGANIZER;CN="Prakashan Korambath":MAILTO:ppk@idre.ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180731T100000
DTEND;TZID=America/Los_Angeles:20180731T120000
DTSTAMP:20260619T211041
CREATED:20180730T155454Z
LAST-MODIFIED:20180730T155923Z
UID:10888-1533031200-1533038400@idre.ucla.edu
SUMMARY:CESMII/UCLA Presentation: Rolling mill exit temperature prediction data contextualization workflow with Matlab and Julia on July 31st 2018 Tuesday @10:00 am in room 3909 MSA (Part I)
DESCRIPTION:We will do a demo of Kepler workflow to contextualize the data used for rolling mill exit temperature prediction.  This will be talk 1 (out of 2) of this series.  We will be running the workflow in 3-way parallel mode.
URL:https://idre.ucla.edu/calendar-event/cesmii-ucla-presentation-rolling-mill-exit-temperature-prediction-data-contextualization-workflow-with-matlab-and-julia-on-july-31st-2018-tuesday-1000-am-in-room-3909-msa-part-i
ORGANIZER;CN="Prakashan Korambath":MAILTO:ppk@idre.ucla.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180726T090000
DTEND;TZID=America/Los_Angeles:20180726T120000
DTSTAMP:20260619T211041
CREATED:20180618T213847Z
LAST-MODIFIED:20180618T213934Z
UID:10838-1532595600-1532606400@idre.ucla.edu
SUMMARY:Principal Components and Exploratory Factor Analysis with SPSS
DESCRIPTION:This seminar will give a practical overview of both principal components analysis (PCA) and exploratory factor analysis (EFA) using SPSS. We will begin with variance partitioning and explain how it determines the use of a PCA or EFA model. For the PCA portion of the seminar\, we will introduce topics such as eigenvalues and eigenvectors\, communalities\, sum of squared loadings\, total variance explained\, and choosing the number of components to extract. For the EFA portion\, we will discuss factor extraction\, estimation methods\, factor rotation\, and generating factor scores for subsequent analyses. The seminar will focus on how to run a PCA and EFA in SPSS and thoroughly interpret output\, using the hypothetical SPSS Anxiety Questionnaire as a motivating example. \nAll researchers are welcome to the workshop. \nRSVP by visiting the following link: RSVP form.
URL:https://idre.ucla.edu/calendar-event/rsvp-principal-components-and-exploratory-factor-analysis-with-spss
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20180719T090000
DTEND;TZID=America/Los_Angeles:20180719T120000
DTSTAMP:20260619T211041
CREATED:20180618T202605Z
LAST-MODIFIED:20180618T213715Z
UID:10836-1531990800-1532001600@idre.ucla.edu
SUMMARY:Applied Survey Data Analysis in Stata 15
DESCRIPTION:This workshop will cover both descriptive and inferential statistics with complex survey data. We will also discuss some graphical methods that can be used with weighted data. \nAll researchers are welcome to the workshop. \nRSVP by visiting the following link: RSVP form.
URL:https://idre.ucla.edu/calendar-event/applied-survey-data-analysis-in-stata-15
END:VEVENT
END:VCALENDAR