Apples or Oranges

Apples or Oranges

Pinar Kaymaz

Pinar Kaymaz

Munich, Bavaria

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

Artificial Intelligence

Description

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 (

). 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\applesororanges.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

Video

Links

Apples or Oranges on Github

Kron228888

Pinar K. added photos to project Apples or Oranges

Medium 2d5024de 7b24 4292 a121 5ab9615c6d9b

Apples or Oranges

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"

3. 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.
>>>

4. 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.

5. 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

Medium kron228888

Pinar K. created project Apples or Oranges

Medium 2d5024de 7b24 4292 a121 5ab9615c6d9b

Apples or Oranges

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 (

). 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\applesororanges.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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