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What are some research papers that every beginner to machine learning should read?

ZeRedz

So I'm trying to get into machine learning and I was wondering what are some research papers that I should read. I'm a complete novice to programming who's mastered only one programming language which is C++.

 

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15 minutes ago, ZeRedz said:

I'm a complete novice to programming who's mastered only one programming language which is C++.

If you've "mastered" c++ you're not a novice...

 

anyway just reading research papers is a bad way to get into a topic you know nothing about. watch some introductory videos first at least.

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19 minutes ago, Sauron said:

If you've "mastered" c++ you're not a novice...

 

anyway just reading research papers is a bad way to get into a topic you know nothing about. watch some introductory videos first at least.

Actually, the reason why I'm asking what research papers a beginner to ML should read is because a course of mine requires us basically write an essay of some sorts and mention a few citations in it from like three or four different research papers.

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4 hours ago, ZeRedz said:

So I'm trying to get into machine learning and I was wondering what are some research papers that I should read. I'm a complete novice to programming who's mastered only one programming language which is C++.

 

You have truly mastered C++, or just consider yourself good enough at it? Those are 2 really different things.

 

Anyway, since you're getting started, I do recommend you to read Rosenblatt's paper on the perceptron (the basis for the current deep learning systems), and from this you can look about how multi layer perceptrons work (sorry, can't recommend a proper paper here).

The next step would be learning how to make those perceptrons actually learn, and the work done by Geoffrey Hinton (one of the godfathers of AI) on backpropagation is extremely relevant. Another paper of his about dropout may also come in handy.

 

You could also take a look at some papers about decision trees, instance-based learning models (such as kNN) and bayesian networks.

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