Name
..
data
figures
00.00-Preface.ipynb
01.00-IPython-Beyond-Normal-Python.ipynb
01.01-Help-And-Documentation.ipynb
01.02-Shell-Keyboard-Shortcuts.ipynb
01.03-Magic-Commands.ipynb
01.04-Input-Output-History.ipynb
01.05-IPython-And-Shell-Commands.ipynb
01.06-Errors-and-Debugging.ipynb
01.07-Timing-and-Profiling.ipynb
01.08-More-IPython-Resources.ipynb
02.00-Introduction-to-NumPy.ipynb
02.01-Understanding-Data-Types.ipynb
02.02-The-Basics-Of-NumPy-Arrays.ipynb
02.03-Computation-on-arrays-ufuncs.ipynb
02.04-Computation-on-arrays-aggregates.ipynb
02.05-Computation-on-arrays-broadcasting.ipynb
02.06-Boolean-Arrays-and-Masks.ipynb
02.07-Fancy-Indexing.ipynb
02.08-Sorting.ipynb
02.09-Structured-Data-NumPy.ipynb
03.00-Introduction-to-Pandas.ipynb
03.01-Introducing-Pandas-Objects.ipynb
03.02-Data-Indexing-and-Selection.ipynb
03.03-Operations-in-Pandas.ipynb
03.04-Missing-Values.ipynb
03.05-Hierarchical-Indexing.ipynb
03.06-Concat-And-Append.ipynb
03.07-Merge-and-Join.ipynb
03.08-Aggregation-and-Grouping.ipynb
03.09-Pivot-Tables.ipynb
03.10-Working-With-Strings.ipynb
03.11-Working-with-Time-Series.ipynb
03.12-Performance-Eval-and-Query.ipynb
03.13-Further-Resources.ipynb
04.00-Introduction-To-Matplotlib.ipynb
04.01-Simple-Line-Plots.ipynb
04.02-Simple-Scatter-Plots.ipynb
04.03-Errorbars.ipynb
04.04-Density-and-Contour-Plots.ipynb
04.05-Histograms-and-Binnings.ipynb
04.06-Customizing-Legends.ipynb
04.07-Customizing-Colorbars.ipynb
04.08-Multiple-Subplots.ipynb
04.09-Text-and-Annotation.ipynb
04.10-Customizing-Ticks.ipynb
04.11-Settings-and-Stylesheets.ipynb
04.12-Three-Dimensional-Plotting.ipynb
04.13-Geographic-Data-With-Basemap.ipynb
04.14-Visualization-With-Seaborn.ipynb
04.15-Further-Resources.ipynb
05.00-Machine-Learning.ipynb
05.01-What-Is-Machine-Learning.ipynb
05.02-Introducing-Scikit-Learn.ipynb
05.03-Hyperparameters-and-Model-Validation.ipynb
05.04-Feature-Engineering.ipynb
05.05-Naive-Bayes.ipynb
05.06-Linear-Regression.ipynb
05.07-Support-Vector-Machines.ipynb
05.08-Random-Forests.ipynb
05.09-Principal-Component-Analysis.ipynb
05.10-Manifold-Learning.ipynb
05.11-K-Means.ipynb
05.12-Gaussian-Mixtures.ipynb
05.13-Kernel-Density-Estimation.ipynb
05.14-Image-Features.ipynb
05.15-Learning-More.ipynb
06.00-Figure-Code.ipynb
Index.ipynb
00.00-Preface.md
01.00-IPython-Beyond-Normal-Python.md
01.01-Help-And-Documentation.md
01.02-Shell-Keyboard-Shortcuts.md
01.03-Magic-Commands.md
01.04-Input-Output-History.md
01.05-IPython-And-Shell-Commands.md
01.06-Errors-and-Debugging.md
01.07-Timing-and-Profiling.md
01.08-More-IPython-Resources.md
02.00-Introduction-to-NumPy.md
02.01-Understanding-Data-Types.md
02.02-The-Basics-Of-NumPy-Arrays.md
02.03-Computation-on-arrays-ufuncs.md
02.04-Computation-on-arrays-aggregates.md
02.05-Computation-on-arrays-broadcasting.md
02.06-Boolean-Arrays-and-Masks.md
02.07-Fancy-Indexing.md
02.08-Sorting.md
02.09-Structured-Data-NumPy.md
03.00-Introduction-to-Pandas.md
03.01-Introducing-Pandas-Objects.md
03.02-Data-Indexing-and-Selection.md
03.03-Operations-in-Pandas.md
03.04-Missing-Values.md
03.05-Hierarchical-Indexing.md
03.06-Concat-And-Append.md
03.07-Merge-and-Join.md
03.08-Aggregation-and-Grouping.md
03.09-Pivot-Tables.md
03.10-Working-With-Strings.md
03.11-Working-with-Time-Series.md
03.12-Performance-Eval-and-Query.md
03.13-Further-Resources.md
04.00-Introduction-To-Matplotlib.md
04.01-Simple-Line-Plots.md
04.02-Simple-Scatter-Plots.md
04.03-Errorbars.md
04.04-Density-and-Contour-Plots.md
04.05-Histograms-and-Binnings.md
04.06-Customizing-Legends.md
04.07-Customizing-Colorbars.md
04.08-Multiple-Subplots.md
04.09-Text-and-Annotation.md
04.10-Customizing-Ticks.md
04.11-Settings-and-Stylesheets.md
04.12-Three-Dimensional-Plotting.md
04.13-Geographic-Data-With-Basemap.md
04.14-Visualization-With-Seaborn.md
04.15-Further-Resources.md
05.00-Machine-Learning.md
05.01-What-Is-Machine-Learning.md
05.02-Introducing-Scikit-Learn.md
05.03-Hyperparameters-and-Model-Validation.md
05.04-Feature-Engineering.md
05.05-Naive-Bayes.md
05.06-Linear-Regression.md
05.07-Support-Vector-Machines.md
05.08-Random-Forests.md
05.09-Principal-Component-Analysis.md
05.10-Manifold-Learning.md
05.11-K-Means.md
05.12-Gaussian-Mixtures.md
05.13-Kernel-Density-Estimation.md
05.14-Image-Features.md
05.15-Learning-More.md
06.00-Figure-Code.md
Index.md
helpers_05_08.py

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