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@@ -23,6 +23,37 @@ Essential codes for jump-starting machine learning/data science with Python
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### Basic interactive controls demo
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* Demo on how to integrate basic interactive controls (slider bars, drop-down menus, check-boxes etc.) in a Jupyter notebook and use them for interactive machine learning task
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## Run Jupyter using Docker
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The https://github.com/machine-learning-helpers/docker-python-jupyter project builds a Docker image so that the (your) Jupyter notebooks can be run out-of-the-box on almost any platform in a few minutes.
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It gives something like:
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Initialization of the Git repository for the Jupyter notebooks:
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$ mkdir -p ~/dev/ml
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$ cd ~/dev/ml
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$ git clone https://github.com/tirthajyoti/PythonMachineLearning.git
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Initialization of the Docker image to run those Jupyter notebooks:
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$ docker pull artificialintelligence/python-jupyter
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Usage:
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$ cd ~/dev/ml/PythonMachineLearning
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$ docker run -d -p 9000:8888 -v ${PWD}:/notebook -v ${PWD}:/data artificialintelligence/python-jupyter
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And then you can open http://localhost:9000 in your browser.
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Any modification to the notebooks may be committed to the Git repository (if you are registered as a contributor), and/or submitted as a pull request.
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Shutdown the Docker image
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$ docker ps
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CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
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431b12a93ccf artificialintelligence/python-jupyter "/bin/sh -c 'jupyt..." 4 minutes ago Up 4 minutes 0.0.0.0:9000->8888/tcp friendly_euclid
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$ docker kill 431b12a93ccf
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**You can [add me on LinkedIn here](https://www.linkedin.com/in/tirthajyoti-sarkar-2127aa7/)**

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