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Julia SciML Symposium

Track :

Programming

Lessons no : 9

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What will you learn in this course?
  • Master Julia SciML tools for building scalable, parallelized scientific machine learning models in Julia environments
  • Apply Julia's computer algebra system for symbolic computation and integrated modeling in scientific research
  • Implement automatic parallelization techniques to optimize large-scale scientific machine learning workflows in Julia
  • Utilize Julia SciML frameworks to enhance accuracy and efficiency in scientific data modeling and simulation
  • Develop custom Julia scripts for symbolic mathematics and automated scientific machine learning processes
  • Analyze complex scientific datasets using Julia's integrated symbolics and parallel computing capabilities

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Lessons | 9


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A modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics .