Welcome to the interactive, multi-channel and collaborative course on Introduction to Scientific Programming and Machine Learning with Julia. There is no registration required. Please use the menu to access a particular section or clone the GitHub course repository on your computer.
Acknowledgements
The Julia part of this course is for the most a reworking, updating and extension of the Julia Concise Tutorial. The ML part takes heavy inspiration from the MITx_6.86x course Machine Learning with Python: from Linear Models to Deep Learning of Regina Barzilay, Tommi Jaakkola and Karene Chu.
The implementation is based on a stack of very flexible documentation packages for Julia, namely Literate.jl, Documenter.jl and QuizQuestions.jl package and, for the ML algorithms, of the BetaML.jl package. Hosting of these pages and of the relative source and automatic building of the pages from source are courtesy of GitHub. Videos are hosted on YouTube.
Financial acknowledgements are reported under each author in the authors section.
Acknowledgements
The Julia part of this course is for the most a reworking, updating and extension of the Julia Concise Tutorial. The ML part takes heavy inspiration from the MITx_6.86x course Machine Learning with Python: from Linear Models to Deep Learning of Regina Barzilay, Tommi Jaakkola and Karene Chu.
The implementation is based on a stack of very flexible documentation packages for Julia, namely Literate.jl, Documenter.jl and QuizQuestions.jl package and, for the ML algorithms, of the BetaML.jl package. Hosting of these pages and of the relative source and automatic building of the pages from source are courtesy of GitHub. Videos are hosted on YouTube.
Financial acknowledgements are reported under each author in the authors section.
