Python basics for machine learning!

Basic machine learning programs can be realized with a few lines of code. To do this one has to understand how one can save numbers, text to a variable and go through this array. The Python basics for machine learning consists of lists, dictionaries and how to go through theses lists or dictionairies using loops or list comprehensions. Once you installed Python you can start with this code.

a= 1
list_of_numbers = [0,1,2,3,4,5]
list_of_characters=['My', 'name', 'is', 'Lorenz']
list_characters_numbers=['I am ', 12, 'years old']

print a, b, list_of_numbers, list_of_characters

The result will be:

1 Loernz [0, 1, 2, 3, 4, 5] [‘My’, ‘name’, ‘is’, ‘Lorenz’]

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Four steps to master machine learning with python (including free books & resources)

To understand and apply machine learning techniques you have to learn Python or R. Both are programming languages similar to C, Java or PHP. However, since Python and R are much younger and “farer away” from the CPU, they are easier. The advantage of Python is that it can be adopted to many other problems than R, which is only used for handling data, analysing it with e.g. machine learning and statistic algorythms and ploting it in nice graphs. Because Python has a broader distribution (hosting websites with Jango, natural language proecssing, accessing APIs of websites such as Twitter, Linkedin etc.) and resembles more classical programming languages like C Python is more popular.

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