This Jupyter Notebook was originally presented at the "ORNL/CNMS Virtual Workshop: AI for Atoms: How to Machine Learn STEM, December 7-10, 2020". It shows how large scanning transmission electron microscopy - differential phase contrast (STEM-DPC) datasets acquired with a fast pixelated electron detector can be analyzed interactively using the open source python library pyXem. A dataset is also included, with the "fe60al40_stripe_pattern.hspy" being the original one. Binned versions of this dataset is also included: - Binned 2 x 2 in the probe dimension: "fe60al40_stripe_pattern_small_dataset.hspy" - Binned 4 x 4 in the probe dimension: "fe60al40_stripe_pattern_very_small_dataset.hspy" Python packages: The notebook was run with - pyxem 0.12.3 - hyperspy 1.6.1 - hyperspy-gui-ipywidgets 1.3.0 - jupyterlab 2.2.9 - ipympl 0.5.8 pyXem information: https://pyxem.github.io/pyxem-website/ HyperSpy information: https://hyperspy.org/ The data is from the journal article "Strain Anisotropy and Magnetic Domains in Embedded Nanomagnets": https://doi.org/10.1002/smll.201904738 The full open dataset and the data processing scripts: https://doi.org/10.5281/zenodo.3466590