01.00-ipython-beyond-normal-python.html
01.01-help-and-documentation.html
01.02-shell-keyboard-shortcuts.html
01.03-magic-commands.html
01.04-input-output-history.html
01.05-ipython-and-shell-commands.html
01.06-errors-and-debugging.html
01.07-timing-and-profiling.html
01.08-more-ipython-resources.html
02.00-introduction-to-numpy.html
02.01-understanding-data-types.html
02.02-the-basics-of-numpy-arrays.html
02.03-computation-on-arrays-ufuncs.html
02.04-computation-on-arrays-aggregates.html
02.05-computation-on-arrays-broadcasting.html
02.06-boolean-arrays-and-masks.html
02.07-fancy-indexing.html
02.09-structured-data-numpy.html
03.00-introduction-to-pandas.html
03.01-introducing-pandas-objects.html
03.02-data-indexing-and-selection.html
03.03-operations-in-pandas.html
03.04-missing-values.html
03.05-hierarchical-indexing.html
03.06-concat-and-append.html
03.07-merge-and-join.html
03.08-aggregation-and-grouping.html
03.10-working-with-strings.html
03.11-working-with-time-series.html
03.12-performance-eval-and-query.html
03.13-further-resources.html
04.00-introduction-to-matplotlib.html
04.01-simple-line-plots.html
04.02-simple-scatter-plots.html
04.04-density-and-contour-plots.html
04.05-histograms-and-binnings.html
04.06-customizing-legends.html
04.07-customizing-colorbars.html
04.08-multiple-subplots.html
04.09-text-and-annotation.html
04.10-customizing-ticks.html
04.11-settings-and-stylesheets.html
04.12-three-dimensional-plotting.html
04.13-geographic-data-with-basemap.html
04.14-visualization-with-seaborn.html
04.15-further-resources.html
05.00-machine-learning.html
05.01-what-is-machine-learning.html
05.02-introducing-scikit-learn.html
05.03-hyperparameters-and-model-validation.html
05.04-feature-engineering.html
05.06-linear-regression.html
05.07-support-vector-machines.html
05.08-random-forests.html
05.09-principal-component-analysis.html
05.10-manifold-learning.html
05.12-gaussian-mixtures.html
05.13-kernel-density-estimation.html
05.14-image-features.html
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