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Knowledge Base Resources

These resources are contributed by researchers, facilitators, engineers, and HPC admins. Please upvote resources you find useful!
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  • Show all (23)
  • (-) documentation (3)
  • (-) visualization (3)
  • ai (2)
  • data-analysis (2)
  • machine-learning (2)
  • plotting (2)
  • allocation-value (1)
  • big-data (1)
  • deep-learning (1)
  • image-processing (1)
  • jupyterhub (1)
  • monte-carlo (1)
  • neural-networks (1)
  • training (1)
  • vectorization (1)

Topics

  • Show all (23)
  • (-) documentation (3)
  • (-) visualization (3)
  • ai (2)
  • data-analysis (2)
  • machine-learning (2)
  • plotting (2)
  • allocation-value (1)
  • big-data (1)
  • deep-learning (1)
  • image-processing (1)
  • jupyterhub (1)
  • monte-carlo (1)
  • neural-networks (1)
  • training (1)
  • vectorization (1)

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Introduction to Vizualization on HPC Using Python
0
  • University of Arizona Workshop Series: Introduction to HPC, Visualization
This workshop has an introduction to the concepts of visualization followed by hands on exercises. The concepts section has Speaker Notes, and the hands on section has an accompanying Jupyter notebook. The workshop is one in a series of Introduction to HPC
visualizationdocumentationtrainingjupyterhub
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Type
learning
Level
Beginner
Data Imputation Methods for Climate Data and Mortality Data
0
  • Data Imputation Methods for Climate Data and Mortality Data - Slices
  • Github repository
  • Data Imputation Methods for Climate Data and Mortality Data - Full Tutorial
This slices and videos introduced how to use K-Nearest-Neighbors method to impute climate data and how to use Bayesian Spatio-Temporal models in R-INLA to impute mortality data. The demos will be added soon.
allocation-valuedocumentationaiplottingvisualizationdata-analysismachine-learning
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Type
video_link
Level
Intermediate, Advanced
Scikit-Learn: Easy Machine Learning and Modeling
0
  • Scikit-learn
Scikit-learn is free software machine learning library for Python. It has a variety of features you can use on data, from linear regression classifiers to xg-boost and random forests. It is very useful when you want to analyze small parts of data quickly.
documentationaiplottingvisualizationbig-datadata-analysisdeep-learningimage-processingmachine-learningmonte-carloneural-networksvectorization
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Type
tool
Level
Beginner, Intermediate