Before getting into the definition, let’s first understand why we need Machine Learning and how it came into existence.
Have you ever thought
- Google Photos has a feature which recognizes the photo / image of a person and categorize or search by name.
- How the emails are classified as Spam or Non-Spam?
When you receive any email in your inbox, it goes through some process, where Gmail, Hotmail, yahoo mail etc. will classify it as spam or non-spam.
- How Google Translate tool or APP will translate to more than 100 languages?
Here i just used “https://translate.google.com/” tool, and tried writing in English and google itself translate into selected language correctly. Similar we can translate into Spanish; Portuguese etc.
Just think how it is done.
- How Siri, Cortana, Alexa etc. give you correct replies?
Siri is from Apple Inc, which works on Apple devices / electronic gadgets which recognizes your voice and responds.
- How products are recommended on the shopping sites?
When you do an online purchase from Amazon or Walmart or any other sites, they will recommend you purchase other products which other customers bought along with the main product.
- How YouTube recommend you the videos based on your recent search?
- Have you ever wondered, how companies like Google; Tesla etc are making Self Driving Cars?
- and many such more…
If you have wondered on these things that how all these are being possible. The answer for all these is Artificial Intelligence and Machine Learning is just one part of Artificial Intelligence.
Now just imagine, are these industries are writing any traditional programs or coding to achieve all these… the answer is BIG no.
They are writing smart program which I will consider as a part of AI / Machine Learning / Deep Learning. Don’t worry about all these jargons. Will get it clear soon.
Companies are training the systems / machines to learn by gaining data or experience. So in-short they are making an algorithm which learns with the experience it gains. Similar to a small kid.
Kids will learn by seeing; experience. First, they see some round object, we (as a parent) tell then it’s for eating and its red in color and it is called as apple. Similar to other objects as well. And next time when they see any new object, they will try to interpret it with the learning they got previously.
Also have you though that why Machine Learning and AI is booming now. Is it a new in market?
So the answer is No… Machine Learning is very old and being used since long. The only difference is that earlier was used and known to very few people and it was very time consuming. In those days collecting the data will take ages, thus Machine Learning never got its reward.
Nowadays data is gathered in minutes or seconds. We have lots of electronic gadgets; Mobile; GPS system in many devices be it Car ; Bike; Mobile; Hand Watch; Electronic Wallet you name it and it is there. All these are generating lots and lots of data to refer.
Thus Machine Learning started booming as data boomed.
Hope this helps you to understand the Machine Learning. Stay tuned, from next blog, in which I will be sharing the essentials for ML, and then will be jumping into the practical part.
Take away :
Features and Target are the two important keywords in ML.
From above example… Features are Shape of Object; Eatable; Color. And Apple is the Target. In next blog will discuss these in detail.
Wikipedia; Google; Google Images
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