henryadams/geometry-of-data

Course "The Geometry of Data" for the AIMS Rwanda Training School, Spring 2023. See the course webpage at math.colostate.edu # geometry-of-data Course "The Geometry of Data" for the AIMS Rwanda Training School, Spring 2023. See the course webpage at math.colostate.edu. The course notes are available at math.colostate.edu. Some of the jupyter notebooks in this GitHub repository are from the "Python Data Science Handbook": oreilly.com. These notebooks include: jakevdp.github.io and jakevdp.github.io and jakevdp.github.io Other jupyter notebooks in this GitHub repository are from scikit-learn: scikit-learn.org. These notebooks include: scikit-learn.org # Installation instructions We will be running a few jupyter notebooks. I recommend doing so locally on your computer. To do so, I first recommend installing Anaconda (anaconda.com). Afterwards, install scikit-learn on your computer, using a terminal command such as "pip install -U scikit-learn". Then, download the course jupyter notebooks (the .ipynb files) from this Course GitHub Page. In your terminal, go to the folder containing these download files, and type "jupyter notebook" in the terminal. This should open a browser, where you can select one of the jupyter notebooks to run, which should open in your browser in a graphical user interface. If the above installation instructions don't yet work for you, please solicit help from somebody with more experience with jupyter notebooks. As a possible back-up plan, you can try skipping the local installation and instead try running things directly in your browser using Colab; see for example the K-means Colab (colab.research. …