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Hello World Machine learning program: - Gateway for ML Being a programmer while learning a new programming language we are all habituated to execute “Hello World” program to have first set of hands on experience which intern works as gateway to master other concepts in a new programming language. But when it is comes to Machine Learning and if you are a programmer like me then you need to understand famous Data Science Venn diagram, before we run our first ML program. ML is the conjunction between Mathematical skill set and Computer Programming skill set. It is pretty easy to develop ML program, just we need to take set of mathematical formula and convert into set of programming instructions, that it we are ready with our ML programming. I’m not kidding, that’s all we need to do. We follow basic below steps to develop an algorithm (for now we are not considering the performance because we are developer we know how to screw up our code) 1. Understand the problem which is going to be solved by an algorithm. 2. Develop logic which is relevant to problem statement. It is needless to mention which kind of problem ML solves. Then Does “Hello World” fits into ML, Intuition behind Hello World ML program is to understand basics knowledge we should have to have hands experience without spending much time.

Way to Learn Machine Learning

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Page 1: Way to Learn Machine Learning

Hello World Machine learning program: - Gateway for ML

Being a programmer while learning a new programming language we are all habituated to execute “Hello World” program to have first set of hands on experience which intern works as gateway to master other concepts in a new programming language.

But when it is comes to Machine Learning and if you are a programmer like me then you need to understand famous Data Science Venn diagram, before we run our first ML program.

ML is the conjunction between Mathematical skill set and Computer Programming skill set. It is pretty easy to develop ML program, just we need to take set of mathematical formula and convert into set of programming instructions, that it we are ready with our ML programming.

I’m not kidding, that’s all we need to do.

We follow basic below steps to develop an algorithm (for now we are not considering the performance because we are developer we know how to screw up our code)

1. Understand the problem which is going to be solved by an algorithm. 2. Develop logic which is relevant to problem statement.

It is needless to mention which kind of problem ML solves.

Then Does “Hello World” fits into ML, Intuition behind Hello World ML program is to understand basics knowledge we should have to have hands experience without spending much time.

Hacking skills is all about programming knowladge, as programmer I belive irresepective of any programming launge it should not bother us to understand the set of instructions in the block of code.

Page 2: Way to Learn Machine Learning

If you are self learner and newbie of Machine Learning like me. Then it will take a quite time to understand to know where to start and how to implement ML concept.

After spending many hours of sleepless nights and going through blogs, many books, many courses, things were not clear what is the starting point for a programmer to start with ML.

Drawback of some of the course, either they concentrate on tools which implements the ML concept assuming audience has the prior mathematical knowledge; else they concentrate on ML concepts without implementation.

This approach is take time consuming. There needs to be overlap between the two concept to make things easier.

Surprisingly Just by refreshing small amount of collage grade probability concepts will help to have hands on experience with ML program

If you are a programmer then coding will not be problem but it is highly necessary to understand how mathematical concepts being used in ML to train the Machines to get the desire output.

There is a famous van diagram which explain what are all quality we need to become a data scientist

Page 3: Way to Learn Machine Learning

Tools to have first hands on Machine Learning program :-

R, Python

Why R and Python not Java tools:-

These are statistical tools which are built on the mathematical background and great thing about these tools are you, they are standalone tools, easy to setup and easy to use. You can have hands on experience with ML case studies without much effort.