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Title: GitHub - Shmuma/PythonDataScienceHandbook: Jupyter Notebooks for the Python Data Science Handbook · GitHub

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Python Data Science Handbookhttp://shop.oreilly.com/product/0636920034919.do
https://github.com/Shmuma/PythonDataScienceHandbook/blob/master/notebooks/figures/PDSH-cover.png
IPythonhttp://ipython.org
NumPyhttp://numpy.org
Pandashttp://pandas.pydata.org
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A Whirlwind Tour of Pythonhttps://github.com/jakevdp/WhirlwindTourOfPython
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Understanding Data Types in Pythonhttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.01-Understanding-Data-Types.ipynb
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Aggregations: Min, Max, and Everything In Betweenhttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.04-Computation-on-arrays-aggregates.ipynb
Computation on Arrays: Broadcastinghttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.05-Computation-on-arrays-broadcasting.ipynb
Comparisons, Masks, and Boolean Logichttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.06-Boolean-Arrays-and-Masks.ipynb
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Text and Annotationhttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.09-Text-and-Annotation.ipynb
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Further Resourceshttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.15-Further-Resources.ipynb
5. Machine Learninghttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.00-Machine-Learning.ipynb
https://github.com/Shmuma/PythonDataScienceHandbook#5-machine-learning
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Introducing Scikit-Learnhttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.02-Introducing-Scikit-Learn.ipynb
Hyperparameters and Model Validationhttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.03-Hyperparameters-and-Model-Validation.ipynb
Feature Engineeringhttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.04-Feature-Engineering.ipynb
In-Depth: Naive Bayes Classificationhttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.05-Naive-Bayes.ipynb
In-Depth: Linear Regressionhttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.06-Linear-Regression.ipynb
In-Depth: Support Vector Machineshttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.07-Support-Vector-Machines.ipynb
In-Depth: Decision Trees and Random Forestshttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.08-Random-Forests.ipynb
In-Depth: Principal Component Analysishttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.09-Principal-Component-Analysis.ipynb
In-Depth: Manifold Learninghttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.10-Manifold-Learning.ipynb
In-Depth: k-Means Clusteringhttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.11-K-Means.ipynb
In-Depth: Gaussian Mixture Modelshttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.12-Gaussian-Mixtures.ipynb
In-Depth: Kernel Density Estimationhttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.13-Kernel-Density-Estimation.ipynb
Application: A Face Detection Pipelinehttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.14-Image-Features.ipynb
Further Machine Learning Resourceshttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/05.15-Learning-More.ipynb
Appendix: Figure Codehttp://nbviewer.jupyter.org/github/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/06.00-Figure-Code.ipynb
https://github.com/Shmuma/PythonDataScienceHandbook#appendix-figure-code
https://github.com/Shmuma/PythonDataScienceHandbook#required-packages
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condahttp://conda.pydata.org
Managing Environmentshttp://conda.pydata.org/docs/using/envs.html
https://github.com/Shmuma/PythonDataScienceHandbook#license
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MIT licensehttps://github.com/Shmuma/PythonDataScienceHandbook/blob/master/LICENSE-CODE
Open Source Initiativehttps://opensource.org/licenses/MIT
https://github.com/Shmuma/PythonDataScienceHandbook#text
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