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https://github.com/drivendata/data-science-is-software


https://github.com/drivendata/data-science-is-software

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README

        

# Data science is Software: #lifehacks for the Jupyer data scientist
----------

### Materials for the 1.5 hr talk: (Updated for ODSC East 2017)

[![ODSC 2017 Video](https://img.youtube.com/vi/HM56wCNxCnQ/0.jpg)](https://www.youtube.com/watch?v=HM56wCNxCnQ)

- [Slides](https://github.com/drivendata/data-science-is-software/blob/master/slides/Data%20Science%20is%20Software%20-%201hr%20lecture%20-%20Slides.pdf)
- [Commandline Demo Script](https://github.com/drivendata/data-science-is-software/blob/master/slides/commandline_script.md)
- [Jupyter Notebook](https://github.com/drivendata/data-science-is-software/blob/master/notebooks/1-hr-lecture.ipynb)
- [Example project that was created during the talk](https://github.com/pjbull/pumps)

```
.
├── data
│   └── raw
│   ├── pumps_train_labels.csv
│   └── pumps_train_values.csv
├── LICENSE
├── notebooks
│   ├── labs
│   │   ├── 2.0-environment-lab.ipynb
│   │   ├── 2.0-environment-solution.ipynb
│   │   ├── 3.0-refactoring-lab.ipynb
│   │   ├── 3.0-refactoring-solution.ipynb
│   │   └── 4.0-testing-lab.ipynb
│   └── lectures
│   ├── 2.0-environment.ipynb
│   ├── 3.0-refactoring.ipynb
│   └── 4.0-testing.ipynb
├── README.md
├── requirements.txt
├── setup.cfg
└── src
├── features
│   ├── build_features.py
│   └── preprocess_solution.py
├── __init__.py
├── mcmc
│   └── hamiltonian.py
├── model
│   └── train_model_solution.py
├── tests
│   ├── example.py
│   ├── __init__.py
│   ├── test_example.py
│   └── test_lab4_solutions.py
└── utils.py
```