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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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  • (-) julia (4)
  • ai (3)
  • machine-learning (3)
  • data-analysis (1)
  • deep-learning (1)
  • neural-networks (1)
  • plotting (1)
  • visualization (1)

Topics

  • Show all (15)
  • (-) julia (4)
  • ai (3)
  • machine-learning (3)
  • data-analysis (1)
  • deep-learning (1)
  • neural-networks (1)
  • plotting (1)
  • visualization (1)

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An Introduction to the Julia Programming Language
0
  • An Introduction to Julia
  • The Julia Computing Language
The Julia Programming Language is one of the fastest growing software languages for AI/ML development. It writes in manner that's similar to Python while being nearly as fast as C++, while being open source, and reproducible across platforms and environments. The following link provide an introduction to using Julia including the basic syntax, data structures, key functions, and a few key packages.
aidata-analysismachine-learningjulia
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Type
learning
Level
Beginner
Data Visualization Tools for Julia
0
  • Visualizations in Julia Using Plots.jl
  • Plotting Options Using Julia
Plots.jl is the most widely used plotting library for the Julia programming language. It's known for being especially powerful in its versatility and intuitiveness. It's limited set of dependencies and wide applicability across different graphics packages make it especially helpful in visualizing the results of your latest Julia implementation. However, there are still multiple options available for Julia programmers to visualize their datasets. The second link details a comparison against a variety of Julia packages.
plottingvisualizationjulia
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Type
tool
Level
Beginner, Intermediate
Neural Networks in Julia
0
  • Neural Networks in Julia using Flux.jl
Making a neural network has never been easier! The following link directs users to the Flux.jl package, the easiest way of programming a neural network using the Julia programming language. Julia is the fastest growing software language for AI/ML and this package provides a faster alternative to Python's TensorFlow and PyTorch with a 100% Julia native programming and GPU support.
aideep-learningmachine-learningneural-networksjulia
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Type
tool
Level
Intermediate, Advanced
Implementing Markov Processes with Julia
0
  • Markov Decision Processes in Julia
The following link provides an easy method of implementing Markov Decision Processes (MDP) in the Julia computing language. MDPs are a class of algorithms designed to handle stochastic situations where the actor has some level of control. For example, used at a low level, MDPs can be used to control an inverted pendulum, but applied in higher level decision making the can also decide when to take evasive action in air traffic management. MDPs can also be extended to the partially observable domain to form the Partially Observable Markov Decision Process (POMDP). This link contains a wealth of information to show one can easily implement basic POMDP and MDP algorithms and apply well known online and offline solvers.
aimachine-learningjulia
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Type
tool
Level
Intermediate, Advanced