“We used to speak two different languages. I would talk about the biology and she would talk about coding. Now we have common ground; we can communicate to each other better. This accelerates our research,”
The gallery of interesting Jupyter notebooks spans a broad range of scientific disciplines including Computer Science, Statistics, Machine Learning, Data Science, Mathematics, Physics, Chemistry, Biology, Earth Science and Geo-Spatial, Linguistics and Text Mining, Signal Processing and more.
In particular, see the reproducible academic publications section.
Finally, an awesome walkthrough of the Python data analysis pipeline from start to finish:
%classpath config resolver scijava.public https://maven.scijava.org/content/groups/public %classpath add mvn net.imagej imagej 2.0.0-rc-71 ij = new net.imagej.ImageJ() ij.io().open("https://imagej.net/images/FluorescentCells.jpg")
Added new repo: scijava.public
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