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5: versions before 19 july. 6: 19 julyaugust versions. julia data science, october. the purposes of this tutorial are ( a) to store things i learn myself about julia and ( b) to help those who want to start coding in julia before reading the 982 pages of the ( outstanding) official documentation. the book is also available freely as static html and pdf at juliadatascience. this document started as a compendium of. intro to probability for data science, november. learning julia: build high- performance applications for scientific computing: this is a comprehensive overview julia tutorial pdf of julia, from syntax basics to writing effective functions, reducing code. jose storopoli, rik huijzer and lazaro alonso.
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