Hello there, Are you interested in Machine Learning? well, you're here, that means you do have interest. That's awesome because Machine Learning is a hot topic these days, It's a new thing.
So, Let's begin, what do we have to know to start learning Machine Leaning.
If you know python that's a plus point for you, if you don't I recommend you to learn python first, because python has a very rich libraries of implementing Machine Learning.
1. What is Machine Learning?
Simply, Machine Learning is something that we use to teach machine.
It's a subfield of Artificial Intelligence.
think of a baby of 3 or 4 years old, who would recognize things as he see it and not think deep into what he see.
think of what would a 4 year baby would say about this picture at first look,
probably he would say
1. sun flower
but we can say that it's a sunset behind the flower and we can also imagine a sunset at Malibu by this picture.
Experts says that Machine Learning is currently can do things what a baby can do, it can recognize image, say whats in it. but it can't feel the beauty of imagination.
2. What can we do with Machine Learning?
As we learn from our past experience, Machine Learning do the same. It learn from past data we given, and by those data it predict the near future.
As basic thing, It can tell the difference between an orange and an apple.
As Advance example, It can predict future sales by looking at previous sales report.
It can predict stock market price by previous data.
3. Machine Learning Problems
Generally we can divide machine learning problems into two parts, those are
1. Classification Problem
2. Regression Problem
1. Classification Problem
Problems where possible output is two or more. This type of problem can be solved using Classification method.
Example. telling if the fruit is an apple or orange by looking at the features of fruit. Like color of the fruit, if the color is orange, it is more likely be an orange than an apple. like this weight of the fruit also matter. as you can see here in this problem there only two possible outcome.
So, it can can be solved by Classification method.
Here is a github link for Iris flower classification problem
https://github.com/sagar03d/ML_Projects/blob/master/Classification.py
Please comment if you have any question, and give feedback about my first ML article. I would love to hear from you.I would post 2nd part soon. Thank you very much.
So, Let's begin, what do we have to know to start learning Machine Leaning.
If you know python that's a plus point for you, if you don't I recommend you to learn python first, because python has a very rich libraries of implementing Machine Learning.
1. What is Machine Learning?
Simply, Machine Learning is something that we use to teach machine.
It's a subfield of Artificial Intelligence.
think of a baby of 3 or 4 years old, who would recognize things as he see it and not think deep into what he see.
think of what would a 4 year baby would say about this picture at first look,
probably he would say
1. sun flower
but we can say that it's a sunset behind the flower and we can also imagine a sunset at Malibu by this picture.
Experts says that Machine Learning is currently can do things what a baby can do, it can recognize image, say whats in it. but it can't feel the beauty of imagination.
2. What can we do with Machine Learning?
As we learn from our past experience, Machine Learning do the same. It learn from past data we given, and by those data it predict the near future.
As basic thing, It can tell the difference between an orange and an apple.
As Advance example, It can predict future sales by looking at previous sales report.
It can predict stock market price by previous data.
3. Machine Learning Problems
Generally we can divide machine learning problems into two parts, those are
1. Classification Problem
2. Regression Problem
1. Classification Problem
Problems where possible output is two or more. This type of problem can be solved using Classification method.
Example. telling if the fruit is an apple or orange by looking at the features of fruit. Like color of the fruit, if the color is orange, it is more likely be an orange than an apple. like this weight of the fruit also matter. as you can see here in this problem there only two possible outcome.
So, it can can be solved by Classification method.
Here is a github link for Iris flower classification problem
https://github.com/sagar03d/ML_Projects/blob/master/Classification.py
Please comment if you have any question, and give feedback about my first ML article. I would love to hear from you.I would post 2nd part soon. Thank you very much.
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