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X-WR-CALDESC:Events for Institute for Quantitative and Computational Biosciences
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DTSTART;TZID=America/Los_Angeles:20190416T093000
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UID:8895-1555407000-1555417800@qcb.ucla.edu
SUMMARY:Machine Learning in Python - Day One
DESCRIPTION:Applications of Machine Learning can be used to analyze biological data without the need of advanced programming skills. For example\, Machine Learning techniques can be used to construct predictive models based on a set of training examples\, to remove noise and spurious artifacts from data (e.g. photobleaching)\, or to help visualize trends within high dimensional datasets\, etc. First\, this workshop introduces the basic principles involved in the applications mentioned above\, such as pattern recognition\, linear and non-linear regression\, and cluster analysis. This workshop will be oriented towards hands-on activities\, starting from the basics of how to load and prepare biological datasets in a Python environment. By the end of this workshop\, students will be able to use Scikit-Learn’s documentation (and other libraries) to build models based on their own data\, assess their performance\, and make new predictions. Although no advanced knowledge will be assumed\, students are encouraged to attend to the Advanced Python and Modern Statistics workshops.
URL:https://qcb.ucla.edu/event/machine-learning-in-python-day-one-3/
LOCATION:The Collaboratory\, 610 Charles E Young Drive East - BOYER HALL ROOM 529\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Interactive Workshop
ATTACH;FMTTYPE=image/png:https://qcb.ucla.edu/wp-content/uploads/sites/14/2019/02/S19-05-W17-Machine-Learning.png
ORGANIZER;CN="QCB Collaboratory":MAILTO:collaboratory@ucla.edu
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DTSTART;TZID=America/Los_Angeles:20190416T133000
DTEND;TZID=America/Los_Angeles:20190416T153000
DTSTAMP:20190226T200601Z
CREATED:20190226T194842Z
LAST-MODIFIED:20190226T200601Z
UID:8898-1555421400-1555428600@qcb.ucla.edu
SUMMARY:Introduction to Modern Statistics - Day One
DESCRIPTION:Workshop attendees will walk away knowing when and how to run modern versions of traditional statistical analysis. First\, this workshop introduces tests and underlying bioinformatical lessons about resampling which are useful to most scientific disciplines. This workshop makes no assumptions about familiarity with traditional statistics; we will simply go through relatable experimental examples and ask how to test various hypotheses\, introducing the relevant methods along the way. Next\, this workshop covers how to best deal with common questions in experimental analysis: What tests can be applied to small sample sizes? When can one assume linearity in the data? What to do with non-Gaussian data / residuals? How does one best detect and justify removing outliers? Which estimators are appropriate with highly non-continuous samples?
URL:https://qcb.ucla.edu/event/introduction-to-modern-statistics-day-one-3/
LOCATION:The Collaboratory\, 610 Charles E Young Drive East - BOYER HALL ROOM 529\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Interactive Workshop
ATTACH;FMTTYPE=image/png:https://qcb.ucla.edu/wp-content/uploads/sites/14/2019/02/S19-06-W14-Intro-to-Modern-Stats.png
ORGANIZER;CN="QCB Collaboratory":MAILTO:collaboratory@ucla.edu
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