It's a big question when one starts with any new learning, especially when there is no direct way to achieve it. I too faced this issue and took a lot of time to figure out the solution and still figuring it out various other things to keep move-on.
When a person steps into the outer world, leaving out the comfort, then comes the real challenge. Where he does not have straight guidance, and our mind will think in multiple directions such as
WHAT? WHERE? WHO? WHEN? WHY? And the biggest thing is HOW?
Same came into my mind as well when I started with Machine Learning.
- What is Machine Learning?
- Why i need to study Machine Learning?
- Where do i start with Machine Learning?
- When to apply Machine Learning and Where?
- How to start?
- Where to start from?
Which tools to use?
And many such questions started in my mind.
With all this I thought of helping others who are going to start with Machine Learning, so that my learning and knowledge on Machine Learning I can share with them and benefit them.
So stay tuned and keep checking my new article on Machine Learning.
Here we will mainly focus on implementing and performing it with a little bit of theoretical part as and where-ever it is required.
To start with Machine Learning, first we need to understand what it is?
In simple terms, Machine Learning is just a study of Business / Domain, Algorithms, Statistical models, Pattern etc, that gives computers the capability to learn without being explicitly programmed.
This means that instead of writing a program by hand for each specific task, we collect lots of examples or experiences belonging to the problem. A Machine Learning algorithm takes all these examples and produces a set of numbers or actions that will be able to do the job. Now these set of numbers or actions is then applied onto the new set of numbers to produce the correct output(s).
Machine Learning is the Scientific Study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is a subset of Artificial Intelligence. Source Wikipedia
I will focus on all these things in my up-coming blogs.
Just a note. I am not a regular writer, here I am just trying to share my experience with friends and new learner to start on ML..
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