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@ -12,9 +12,6 @@
## Index ## Index
* [spark](#spark)
* [mapreduce-python](#mapreduce-python)
* [kaggle-and-business-analyses](#kaggle-and-business-analyses)
* [deep-learning](#deep-learning) * [deep-learning](#deep-learning)
* [scikit-learn](#scikit-learn) * [scikit-learn](#scikit-learn)
* [statistical-inference-scipy](#statistical-inference-scipy) * [statistical-inference-scipy](#statistical-inference-scipy)
@ -22,6 +19,9 @@
* [matplotlib](#matplotlib) * [matplotlib](#matplotlib)
* [numpy](#numpy) * [numpy](#numpy)
* [python-data](#python-data) * [python-data](#python-data)
* [kaggle-and-business-analyses](#kaggle-and-business-analyses)
* [spark](#spark)
* [mapreduce-python](#mapreduce-python)
* [amazon web services](#aws) * [amazon web services](#aws)
* [command lines](#commands) * [command lines](#commands)
* [misc](#misc) * [misc](#misc)
@ -31,47 +31,6 @@
* [contact-info](#contact-info) * [contact-info](#contact-info)
* [license](#license) * [license](#license)
<br/>
<p align="center">
<img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/spark.png">
</p>
## spark
IPython Notebook(s) demonstrating spark and HDFS functionality.
| Notebook | Description |
|--------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|
| [spark](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/spark/spark.ipynb) | In-memory cluster computing framework, up to 100 times faster for certain applications and is well suited for machine learning algorithms. |
| [hdfs](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/spark/hdfs.ipynb) | Reliably stores very large files across machines in a large cluster. |
<br/>
<p align="center">
<img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/mrjob.png">
</p>
## mapreduce-python
IPython Notebook(s) demonstrating Hadoop MapReduce with mrjob functionality.
| Notebook | Description |
|--------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|
| [mapreduce-python](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/mapreduce/mapreduce-python.ipynb) | Runs MapReduce jobs in Python, executing jobs locally or on Hadoop clusters. Demonstrates Hadoop Streaming in Python code with unit test and [mrjob](https://github.com/Yelp/mrjob) config file to analyze Amazon S3 bucket logs on Elastic MapReduce. [Disco](https://github.com/discoproject/disco/) is another python-based alternative.|
<br/>
<p align="center">
<img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/kaggle.png">
</p>
## kaggle-and-business-analyses
IPython Notebook(s) used in [kaggle](https://www.kaggle.com/) competitions and business analyses.
| Notebook | Description |
|-------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------|
| [titanic](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/kaggle/titanic.ipynb) | Predicts survival on the Titanic. Demonstrates data cleaning, exploratory data analysis, and machine learning. |
| [churn-analysis](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/analyses/churn.ipynb) | Predicts customer churn. Exercises logistic regression, gradient boosting classifers, support vector machines, random forests, and k-nearest-neighbors. Discussion of confusion matrices, ROC plots, feature importances, prediction probabilities, and calibration/descrimination.|
<br/> <br/>
<p align="center"> <p align="center">
<img src="http://i.imgur.com/ZhKXrKZ.png"> <img src="http://i.imgur.com/ZhKXrKZ.png">
@ -230,6 +189,47 @@ IPython Notebook(s) demonstrating Python functionality geared towards data analy
| [pdb](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/python-data/pdb.ipynb) | Learn how to debug in Python with the interactive source code debugger. | | [pdb](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/python-data/pdb.ipynb) | Learn how to debug in Python with the interactive source code debugger. |
| [unit tests](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/python-data/unit_tests.ipynb) | Learn how to test in Python with Nose unit tests. | | [unit tests](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/python-data/unit_tests.ipynb) | Learn how to test in Python with Nose unit tests. |
<br/>
<p align="center">
<img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/kaggle.png">
</p>
## kaggle-and-business-analyses
IPython Notebook(s) used in [kaggle](https://www.kaggle.com/) competitions and business analyses.
| Notebook | Description |
|-------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------|
| [titanic](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/kaggle/titanic.ipynb) | Predicts survival on the Titanic. Demonstrates data cleaning, exploratory data analysis, and machine learning. |
| [churn-analysis](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/analyses/churn.ipynb) | Predicts customer churn. Exercises logistic regression, gradient boosting classifers, support vector machines, random forests, and k-nearest-neighbors. Discussion of confusion matrices, ROC plots, feature importances, prediction probabilities, and calibration/descrimination.|
<br/>
<p align="center">
<img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/spark.png">
</p>
## spark
IPython Notebook(s) demonstrating spark and HDFS functionality.
| Notebook | Description |
|--------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|
| [spark](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/spark/spark.ipynb) | In-memory cluster computing framework, up to 100 times faster for certain applications and is well suited for machine learning algorithms. |
| [hdfs](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/spark/hdfs.ipynb) | Reliably stores very large files across machines in a large cluster. |
<br/>
<p align="center">
<img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/mrjob.png">
</p>
## mapreduce-python
IPython Notebook(s) demonstrating Hadoop MapReduce with mrjob functionality.
| Notebook | Description |
|--------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|
| [mapreduce-python](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/mapreduce/mapreduce-python.ipynb) | Runs MapReduce jobs in Python, executing jobs locally or on Hadoop clusters. Demonstrates Hadoop Streaming in Python code with unit test and [mrjob](https://github.com/Yelp/mrjob) config file to analyze Amazon S3 bucket logs on Elastic MapReduce. [Disco](https://github.com/discoproject/disco/) is another python-based alternative.|
<br/> <br/>
<p align="center"> <p align="center">
<img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/aws.png"> <img src="https://raw.githubusercontent.com/donnemartin/data-science-ipython-notebooks/master/images/aws.png">