Introduction to Machine Learning

Machine Learning is quite a big word for me. And I am just starting to soak my feet in that vast ocean of knowledge. I googled many times with different keyword to understand what exactly is Machine Learning. I was looking for something in absolutely layman’s terms and here is my take away from all my “Research”.


What is Machine Learning?

We, Humans, learn from our Experiences (at least we are supposed to do so). When a Machine starts learning from Experiences, that is Machine Learning. The only difference is for a machine, the Experience is called “DATA”. So, a system can learn, improve, and even predict from some Data without being explicitly programmed. My common sense says, more the volume of the data, better will be the prediction.


Examples of Machine Learning:

We encounter tons of examples of Machine Learning in our daily lives without actually realizing it.


1. Search Engine:

If I search for “places to eat near me” (which I do often), the search results can be different from my neighbor who is searching for the same. The Ranking of the pages is based on what I will most likely click on. That prediction/decision is based on DATA from my previous click history may be. But, that is Machine Learning.


 2. E-Commerce:

Whenever I open the Amazon App, it shows some sections like “More Items to consider” or “Your Recommendations” even before I start browsing for something and needless to say, I end up buying too. See, that is the beauty of Machine Learning.


3. Social Networking Sites:

If we open Facebook or LinkedIn, we can see the suggestions for “People You May Know”. Also, If we add a Photo on Facebook, it can Tag the other persons immediately, on its own. So, even Suggested Friends or Tag a friend is Machine Learning.


4. Netflix Recommendations:

When I finish watching a show on Netflix, I just check for the Netflix Recommendations with a better percentage match. It saves me time and there is where I am using Machine Learning.


5. Inbox or Spam:

Some of my emails go to the Inbox folder and some to my Spam folder. How does that happen? Again, the answer is Machine Learning.

Conclusion:

Needless to say, we all are using Machine Learning in our day to day life. Is it always accurate? Maybe not! Some of my important emails may get hidden in the SPAM folder or I may start watching a Netflix Recommended movie and I could not watch 10 mins since it is not as per my taste.So, what the Machine suggested is based on some Data. The system uses that Data runs some methods or Algorithms and gets us a resultset. The accuracy of Data, the amount of data, the selection of Algorithms, all play a vital role in that Prediction. Thus, the Machine improves on learning and hence predicting based on the DATA.  So, as per my understanding:

“Machine Learning is all about Predictions from some data.”

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