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Site Navigation

  • About
  • OceanHackWeek 2024
  • Resources
    • Past OHW Events
  • GitHub
  • Discussions
  • Twitter
  • YouTube
  • Email
OceanHackWeek
Data Science + Oceanography + Fisheries

Section Navigation

  • OceanHackWeek 2023 (OHW23)
    • Schedule
    • Organizers
    • Logistics
      • Getting Help
    • Tutorials
      • Getting started on tutorials
      • Data Access Methods
      • Machine learning
        • The dataset
        • A quick introduction to machine learning
        • Unsupervised learning part 2: kmeans
        • Supervised learning
      • AI-Assisted Programming
      • Xarray in 45 minutes
      • Meta’omics for Ocean Science
    • Projects
      • OHW23 Projects List
    • Information for Applicants
  • OceanHackWeek 2022 (OHW22)
    • Schedule
    • Global Virtual Event
    • Regional Satellite Events
      • US Northeast
      • US Northwest
      • US Southwest
      • Australia
      • Brazil
      • Español
        • English Description
    • Organizers
    • Logistics
      • Getting Help
    • Tutorials
      • Getting started on tutorials
      • Xarray in 45 minutes
      • Data access in Python
        • Data Access
        • Extras: load netCDF files directly from HTTPS
        • Data Clean Up (QARTOD)
        • First create the erddapy object
      • Data access in R
        • 1) ERDDAP
        • National Data Buoy Center
        • Load packages
      • Data visualization in Python
        • Index and Schedule
        • Getting set up
        • Welcome to HoloViz!
        • pn.interact
        • Widgets and reactive components
        • Read in the data
        • Read in the data
      • Machine learning applications
        • A quick introduction to machine learning
        • Unsupervised learning part 2: kmeans
        • Supervised learning
      • Espanol Tutorials
        • Python Cientifico
        • Lectura de datos
      • Managing conda environments
    • Projects
      • OHW22 Projects List
    • Information for Applicants
  • About
  • Tutorials
  • Machine learning

Machine learning#

  • The dataset
  • A quick introduction to machine learning
    • ML will solve all of our problems, right?
    • What is Machine Learning (ML)?
    • Vocabulary
    • Unsupervised: PCA
    • Summary
  • Unsupervised learning part 2: kmeans
  • Features
  • What are we missing?
  • ⚠️Negative Results Alert⚠️
  • Supervised learning
  • Validation

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