/cd0372-Applying-AI-to-EHR-Data

Exercise and Project code for newly disaggregated course from ND320-3

Primary LanguageJupyter NotebookMIT LicenseMIT

If you want to download course exercises/project files to your local computer, instead of using the provided workspaces, you will find the information below helpful.

Lesson Folder

This repo contains a folder for each lesson and one project folder.

Example

lesson-1-hello
lesson-2-world
lesson-3-foo
lesson-4-bar
project

Each lesson folder is named using the naming convention of lesson-#-name-of-lesson.

Example

lesson-1-hello

Exercises Folder

Each lesson folder contains an exercises folder. This exercises folder should contain all files and instructions necessary for the exercises along with the solution. The solutions for these exercises will be shared with students. See the README in the exercises folder for information about folder structure.

Project Folder

The project folder should contain all files and instructions necessary for setup. If possible, a set of instructions should be provided for both Udacity workspaces and a way to work locally (for both MacOS and Windows OS). At a minimum, one set of instructions should be provided. A README template has been provided in the project folder. This template layout should be used to write your README.

Getting Started

Instructions for how to get a copy of the project running on your local machine.

Dependencies

Using Anaconda consists of the following:

  1. Install miniconda on your computer, by selecting the latest Python version for your operating system. If you already have conda or miniconda installed, you should be able to skip this step and move on to step 2.
  2. Create and activate * a new conda environment.

* Each time you wish to work on any exercises, activate your conda environment!

1. Installation

Download the latest version of miniconda that matches your system.

Linux Mac Windows
64-bit 64-bit (bash installer) 64-bit (bash installer) 64-bit (exe installer)
32-bit 32-bit (bash installer) 32-bit (exe installer)

Install miniconda on your machine. Detailed instructions:

2. Create and Activate the Environment

For Windows users, these following commands need to be executed from the Anaconda prompt as opposed to a Windows terminal window. For Mac, a normal terminal window will work.

Getting Started

Follow the instructions in starter_code/student_project.ipynb and be sure to set up your Anaconda environment to get started!

Dependencies

Using Anaconda consists of the following:

  1. Install miniconda on your computer, by selecting the latest Python version for your operating system. If you already have conda or miniconda installed, you should be able to skip this step and move on to step 2.
  2. Create and activate * a new conda environment.

* Each time you wish to work on any exercises, activate your conda environment!

1. Installation

Download the latest version of miniconda that matches your system.

Linux Mac Windows
64-bit 64-bit (bash installer) 64-bit (bash installer) 64-bit (exe installer)
32-bit 32-bit (bash installer) 32-bit (exe installer)

Install miniconda on your machine. Detailed instructions:

2. Create and Activate the Environment

For Windows users, these following commands need to be executed from the Anaconda prompt as opposed to a Windows terminal window. For Mac, a normal terminal window will work.

Git and version control

These instructions also assume you have git installed for working with Github from a terminal window, but if you do not, you can download that first with the command:

conda install git

If you'd like to learn more about version control and using git from the command line, take a look at our free course: Version Control with Git.

Now, we're ready to create our local environment!

  1. Clone the repository, and navigate to the downloaded folder. This may take a minute or two to clone due to the included image data.
git clone https://github.com/udacity/nd320-c1-emr-data-starter.git
cd nd320-c1-emr-data-starter

  1. Create (and activate) a new environment, named udacity-ehr-env with Python 3.7. If prompted to proceed with the install (Proceed [y]/n) type y.

    • Linux or Mac:
    conda create -n udacity-ehr-env python=3.7
source activate udacity-ehr-env
    • Windows:
    conda create --name udacity-ehr-env python=3.7
activate udacity-ehr-env

    At this point your command line should look something like: (udacity-ehr-env) <User>:USER_DIR <user>$. The (udacity-ehr-env) indicates that your environment has been activated, and you can proceed with further package installations.

  2. Install a few required pip packages, which are specified in the requirements text file. Be sure to run the command from the project root directory since the requirements.txt file is there. I also added a line for installing the environment in your notebook in case this is new for you. You should be able to now look for the environment when you select the kernel.

pip install -r requirements.txt
ipython3 kernel install --name udacity-ehr-env --user

License

This project is licensed under the MIT License - see the LICENSE.md

Git and version control

These instructions also assume you have git installed for working with Github from a terminal window, but if you do not, you can download that first with the command:

conda install git

If you'd like to learn more about version control and using git from the command line, take a look at our free course: Version Control with Git.

Now, we're ready to create our local environment!

  1. Clone the repository, and navigate to the downloaded folder. This may take a minute or two to clone due to the included image data.
git clone https://github.com/udacity/AIHCND_C1.git
cd AIHCND_C1

  1. Create (and activate) a new environment, named udacity-ehr-env with Python 3.7. If prompted to proceed with the install (Proceed [y]/n) type y.

    • Linux or Mac:
    conda create -n udacity-ehr-env python=3.7
source activate udacity-ehr-env
    • Windows:
    conda create --name udacity-ehr-env python=3.7
activate udacity-ehr-env

    At this point your command line should look something like: (udacity-ehr-env) <User>:AIHCND_C1 <user>$. The (udacity-ehr-env) indicates that your environment has been activated, and you can proceed with further package installations.

  2. Install a few required pip packages, which are specified in the requirements text file. Be sure to run the command from the project root directory since the requirements.txt file is there.

pip install -r requirements.txt