Learn some basic machine learning techniques on both boolean and text data using python, sklearn, and jupyter notebooks.

• Jupyter Notebooks
• git bash
• python
• pip
• scikit-learn

Before you begin, you'll need to install a few packages and applications in order to create machine learning solutions and visuals. The tools that will be used in this guide include Jupyter Notebooks for visualizing and interacting with your code and displaying results, Scikit-Learn for machine learning functions, matplotlib for creating different graphs and visuals, and pandas to interact with our data. Let's start by installing everything we need.

1. Install Python Download the correct Python version (python2 or python3) for your machine. Follow the command prompts on the installer.

   https://www.python.org/downloads/

2. Open up Powershell In your search bar in the bottom home ribbon, type "Powershell" and select the "Windows Powershell" application. This will open up a blue window where you can type in basic commands.

3. Find the python folder Locate where your newly downloaded python folder is located. You can do this by opening up your file explorer and searching for "python". Once it is found, copy the file path of the newly downloaded python folder. In the powershell command prompt, type

    cd [insert your file path here - do not include it in brackets]
   

   and hit enter. The file path will look somewhat similar to this (note: it may have more things in between C:\Users\ and \Python\Python37-32 *** the numbers at the end of the last part (37-32) are specific to the version of python you downloaded):

    cd C:\Users\jdoe\Programs\Python\Python37-32
   

   To ensure that python is installed correctly, type

    python --version
   

   it will display the version you have installed or an error if you don't have it installed/your file path you provided is incorrect.

4. Install pip Pip is a tool that allows you to install all kinds of python packages and libraries. Navigate to https://bootstrap.pypa.io/get-pip.py and copy the contents to a text file on your local machine (use notepad - paste the contents into here). Save the file as "get-pip.py" and save the file inside of your python folder. Return back to your powershell prompt and type

    python get-pip.py
   

   This will install the pip package which includes some other important files. To ensure it installed correctly, type "pip --version". Update the pip package by typing "python -m pip install -U pip".

5. Install common ML packages In the powershell prompt type the following commands, ensuring that they successfully install before you type the next command:

    pip install numpy
    pip install scipy
    pip install matplotlib
    pip install statsmodels
    pip install pandas
    pip install jupyter
   

6. Install Git Bash In your internet browser, navigate to https://gitforwindows.org/ to download git bash for windows.

Now that you have everything installed, it's time to clone the github repository. Add a new folder to your desired location and give it a descriptive name. Go into your newly created folder and copy the file path. Now open up git bash and type

git clone https://github.com/mawebster9/MachineLearningMadeEasy

and hit enter. This will pull a copy of the repository onto your machine. It is recommended to copy the repo into your python folder.

For additional git bash help, visit https://www.atlassian.com/git/tutorials/git-bash for help with navigating through git bash.

For aditional git help, visit http://guides.beanstalkapp.com/version-control/common-git-commands.html for help with git itself.

Git mimics Linux file structure definitions, so for Windows machines you will need to replace all of the "" to "/"" (example: "C:\Users\Programs\git_repo" should be changed to this "C:/Users/Programs/git_repo") in the file path when using git bash. This is a problem with Windows machines since the directory paths have different syntax structures. You also need to include all file folders and files in double quotes ("Example File Name") if they are not one single word and are broken up by spaces.

Now that you have everything installed, it's time to run the Jupyter Notebooks application. The most important part of this step is to not exit/close out of the powershell window - this will stop the notebook. You can minimize this window but do not close it. As you make changes to the notebook in your browser window, code will be populated in the powershell window but you can ignore this for now.

In the Powershell window, change your directory to be your python folder. I recommend cloning your git repository in this folder. In the powershell command prompt, type

jupyter notebook

You will see output that resembles this:

[I 10:52:50.055 NotebookApp] The Jupyter Notebook is running at:
[I 10:52:50.057 NotebookApp] http://localhost:8888/?token=a59f01953665fe6bb67a64e21ff20d395a8be1ab582813ea
[I 10:52:50.057 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 10:52:50.169 NotebookApp]

This command may automatically open your browser - if it does not, open up a browser and in the website bar type "http://localhose:8888" and hit enter. It will either open directly to the files available to you but if it does not, copy the remaining line after the "token=" on the second line of the output and paste it into the token box on the webpage and hit enter.

Now you have an instance of Jupyter Notebooks on your computer!

To start a new Notebook, select the "New" option at the top and under the "Notebook:" option, select "Python 3". This will open up a new notebook for you. If you wish to access already existing Notebooks, simply click on the notebook you wish to open.

Make sure to save your files often and push any of your changes to git often. I highly recommend you thoroughly document your code to ensure you and others can easily understand what's going on.

If you did not clone the repo into your Python folder, you will need to locate the files you want, copy them to the python folder, follow directions for getting Jupyter Notebooks up and running, do your work, save, then copy all files you changed back to the repo folder, then push changes to git if you wish.