Everything Thing About Machine Learning Open Sourced

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Summary
In simple words, this project is for people interested in Machine Learning but have no idea where to start from.

This project was built for those interested in Machine Learning. It contains explanations of common Machine Learning Concepts like Supervised Learning, unsupervised Learning, Reinforcement Learning, Time Series, Computer Vision, NLPs etc.

If you have any Knowledge at all of Machine Learning anything at all from knowing the right spelling of the word Machine Learning to having a good grasp of a newly introduced Model Architecture then you should know that there is someone out there who needs your expertise and it all boils down to a will you help the community or will you not. if yes then visit then view the project https://github.com/EdemGold/Nutshell_Machinelearning

Anything can be contributed as long as it concerns Machine Learning.

Imagine a scenario where you can learn about Machine Learning and all the big-sounding words and concepts are explained with code!

A place where you can see explanations about things like Supervised Learning, Unsupervised Learning, Natural Language Processing, Computer Vision and also see the code for them being run and it's open-source so anyone can contribute to it.

Inspiration Behind the Project

I feel a lot of people fear Machine Learning and a lot of that fear is based on unnecessary things like:

A fear of Math

Lack of Understanding of the complex concepts

Now don't get me wrong Math and Complex words are a big part off Machine Learning.

The Algorithms used in Machine Learning are largely based on Math Concepts and those complex words are the explanations for the building blocks in Machine Learning.

But that doesn't mean you need to have a degree in advanced math and statistics before you can do Machine Learning in essence once you have a computer, internet access, a web browser you can build a machine Learning model.

In simple words, this project was built for people interested in Machine Learning but have no idea where to start from.

Mission of the project
This project was built for those interested in Machine Learning. It contains explanations of common Machine Learning Concepts like Supervised Learning, unsupervised Learning, Reinforcement Learning, Time Series, Computer Vision, NLPs etc.

The repo contains coded explanations for the different concepts because a lot of people prefer to learn through code rather than simply reading about the concepts.

In simple words, this repo was Built by the Machine Learning Community for the Machine Learning Community.

Project Architecture
The project repository was built with a tree like structure in mind.

It contains folders inside folders.

For example, in the supervised Learning folder you will find classification and regression folders (classification and regression are sub sets or components of Supervised learning).

Each Folder contains a .txt file called "introduction to folder" which talks about the folder and all the stuff contained in that folder.

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Why Should You Contribute
I will keep this simple, If you have any Knowledge at all of Machine Learning anything at all from knowing the right spelling of the word Machine Learning to having a good grasp of a newly introduced Model Architecture then you should know that there is someone out there who needs your expertise and it all boils down to a will you help the community or will you not. if yes then click here.

Contribution Guidelines
If you want to create a new folder, please create a .txt file in the folder you want to create and name it "introduction to folder" and in it write out what the folder will contain; concepts you'll cover, code that will be written, language used, packages to be installed etc. This is done so developers who aren't familiar with the content in the folder can understand what it's about.

All code contributions should have explanations.

Code can be contributed using jupyter notebooks and .py, .r or .jl files. But jupyter notebooks will be much appreciated because they support clear explanation of code.

All code contributed should concern Machine Learning in one way or another.

What can you Contribute
Anything can be contributed as long as it concerns Machine Learning.

If you can't contribute code them you can help fix a typo just make sure you contribute where it's needed.

It's our responsibility as a community to help each other. Knock yourself out.

Click on this link https://github.com/EdemGold/Nutshell_Machinelearning to view the project