BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//NJBDA - New Jersey Big Data Alliance - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:NJBDA - New Jersey Big Data Alliance
X-ORIGINAL-URL:https://njbda.org
X-WR-CALDESC:Events for NJBDA - New Jersey Big Data Alliance
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20210314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20211107T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20220313T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20221106T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20230312T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20231105T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220311T140000
DTEND;TZID=America/New_York:20220311T170000
DTSTAMP:20260421T125730
CREATED:20220208T143910Z
LAST-MODIFIED:20220315T203001Z
UID:1129-1647007200-1647018000@njbda.org
SUMMARY:Data Science Workshop: Machine Learning with Python
DESCRIPTION:Watch the recording by clicking on the image above\n\n\n\nIn the last few years\, both industry and academia witnessed the rise of Machine Learning (ML) methods being applied in finance\, marketing\, retails\, science\, engineering\, healthcare\, and humanities. Learning how to apply ML methods to a domain specific application does not require a detailed knowledge about the inner machinery of these methods; however\, one needs to learn the best practices and recommendations followed by the community. \n\n\n\nIn this workshop\, after a brief overview on machine learning\, we will focus on doing the hands-on training in applying ML models on various data types including image\, text\, and time series. We will work through the use cases of classification and regression problems and discuss where to apply supervised or unsupervised methods. \n\n\n\nObjective of the workshop \n\n\n\nUnderstand supervised and unsupervised methodsChoose correct metrics and sampling methods for classification vs regression problemsFind out which features are important in a given datasetLearn to apply ML models such as Decision Trees\, Random Forest\, and Support Vector MachinesPerform clustering and dimensionality reductions (PCA\, t-SNE\, K-means\, etc.)Search the parameter space – hyperparameter optimization\n\n\n\nWhat is needed? Laptop/Desktop with Internet connection \n\n\n\nDuration: 3 hours \n\n\n\nLevel: Intermediate \n\n\n\nProgramming Platform: On-line resource or Laptop. Instructions for on-line resources will be given in the workshop. \n\n\n\nPrerequisite: Basic laptop usage. Basic knowledge of Python is helpful for doing the hands-on session. \n\n\n\nSlides and materials: Will be provided in the workshop \n\n\n\nThis workshop is hosted by the Office of Advanced Research Computing (OARC)\, Rutgers University\, organized by Bala Desinghu in collaboration with the Eastern Regional Network (ERN) and the New Jersey Big Data Alliance (NJBDA). \n\n\n\nParticipants are encouraged to attend with campus partners representing a variety of stakeholders for campus research and research computing (e.g.\, researchers\, research computing professionals\, students\, staff\, faculty\, and practitioners\, etc.). \n\n\n\nFor additional information\, feel free to contact bala.desinghu@rutgers.edu\, forough.ghahramani@njedge.net\, or gavirapp@kean.edu.
URL:https://njbda.org/event/data-science-workshop-machine-learning-with-python-and-scikit-learn/
LOCATION:New Jersey
CATEGORIES:workshops
END:VEVENT
END:VCALENDAR