Apples or Oranges

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Simple machine learning project which guesses if the given input falls into the correct class. ...learn more

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Overview / Usage

For quite some time now, I have been interested in machine learning. Although I completed a machine learning project for my Bachelor's Thesis which was in MATLAB, I really want to have some hands on experience in Python, too.

So I went ahead and searched for some introductory courses online and I've found Mr. Josh Gordon's awesome video "Hello World - Machine Learning Recipes #1" on Youtube (https://www.youtube.com/watch?v=cKxRvEZd3Mw). It's a supervised learning project which creates a classifier from examples.

You can access sourcecode in my repository on Github -> https://github.com/pinarkaymaz6/python-supervised-learning

For the absolute beginners like myself, here's some tips to install Python and reqired libraries.

  1. Download Anaconda from here: https://www.continuum.io/downloads
    I downloaded Python 3.6 version.

  2. Add Anaconda into Path.
    Control Panel\System and Security\System > Advanced System Settings > Advanced Tab > Environment Variables> System Variables

Find "Path" variable and add Anaconda3 file path. For me, it was "C:\Users\PINAR\Anaconda3"

  1. Open Command Prompt to check Python is successfully installed. Type "python". If you can see the version, everything is okay so far. You can close this terminal now.

C:\Users\PINAR>python
Python 3.6.1 |Anaconda 4.4.0 (32-bit)| (default, May 11 2017, 14:16:49) [MSC v.1900 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.

  1. Create your Python project and copy the source code. It's a simple text file with .py extention. Or, you can download sourcecode from my Github profile.

  2. Open Command Prompt and run your code. Congrats!

python C:\Users\PINAR\Anaconda3\apples_or_oranges.py

Now, I want to develop this project adding statistical analysis. I want to analyse in what ratio this machine can successfully detect apples or oranges. Also I want to add some features to improve these detection results.

Anyone who wants to contribute is more than welcome!

Pınar

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