About mllibs

Some key points about the library:

• mllibs is a Machine Learning (ML) library which utilises natural language processing (NLP)
• Development of such helper modules are motivated by the fact that everyones understanding of coding & subject matter (ML in this case) may be different
• Often we see people create functions and classes to simplify the process of code automation (which is good practice)
• Likewise, NLP based interpreters follow this trend as well, except, in this case our only inputs for activating certain code is natural language
• Using python, we can interpret natural language in the form of string type data, using natural langauge interpreters
• mllibs aims to provide an automated way to do machine learning using natural language

Code Automation

Types of Approaches

There are different ways we can automate code execution:

• The first two (function,class) should be familiar, such approaches presume we have coding knowledge.
• Another approach is to utilise natural language to automate code automation, this method doesn't require any coding knowledge.

Function

Function based code automation should be very familiar to people who code, we define a function & then simply call the function, entering any relevant input arguments which it requires, in this case n

def fib_list(n):
    result = []
    a,b = 0,1
    while a<n:
        result.append(a)
        a,b = b, a + b
    return result

fib_list(5) 

Class

Another common approach to automate code is using a class based approach. Utilising OOP concepts we can initialise & then call class methods in order to automate code:

class fib_list:
    
    def __init__(self,n):
        self.n = n

    def get_list(self):
        result = []
        a,b = 0,1
        while a<self.n:
            result.append(a)
            a,b = b, a + b
        return result

fib = fib_list(5)
fib.get_list()

Natural Language

Another approach, which mllibs uses in natural language based code automation:

input = 'calculate the fibonacci'
         sequence for the value of 5'

nlp_interpreter(input) 

All these methods will give the following result:

[0, 1, 1, 2, 3]

Library Contents

mllibs is constantly evolving and has a repository documentation and development page which you can visit, mllibs documentation

How to Contribute

Predefined Tasks

I'm constantly looking for people to contribute to the development of the library. I've created a page where I set different tasks that you can do and join the mllibs group, if you are interested, please get in touch me on telegram shtrauss2 or via shtrausslearning

Our own ideas and contributions

Here's how you can get started:

1. Fork the repository
2. Create a new branch for your changes
3. Make your changes and commit them
4. Submit a pull request