Case Study on how Machine Learning is used by Facebook!
What comes first to mind when you think about social networking?
It's obviously Facebook!
But did you know internally Facebook uses machine learning?
Now let's study of Facebook uses machine learning!
- You will see some of the accounts and they show that these are the people you may know, Obviously they are right most of them we know in our daily life. But do you think how Facebook comes to know this?
- The core behind this is machine learning, it analysis our profile, our interests, our friends, our likes, and our friends of friends from these it will predict and say these people you may know!
Let's see some of the ways how machine learning is used in Facebook.
- Facial recognition
You know it's hard for us to identify our friend's post under huge makeup!
But Facebook will do it for us with the help of machine learning.
We get a notification that you have tagged in so and so post, internally facial recognition module /algorithm of machine learning recognizes you and sends notification to us.
We may wonder what we searched on myntra , Flipkart, Amazon, etc.. we will see their ads on our Facebook page.
The core behind this is again machine-learning.
This is done using deep neural networks that analyze your age, gender, location, page likes, interests, and even your mobile data to profile you into select categories and then show you ads specifically targeted towards these categories.
For Example, Suppose that the data collected from your online interests, field of study, shopping history, restaurant choices, etc. profiles you in the category of young fashionista according to the Facebook deep neural networks algorithm. Then the ads you are shown will likely cater to this category so that you get the most relevant and useful ads that you are most likely to click.
* Language Translation
We know that almost every person has a Facebook account! and there is no chance that all the people are able to speak and write in English.
So Facebook came up with see translation, by clicking it we can change our language to our user-friendly language (ex: Hindi, Telugu, etc ).
The Facebook translator accomplishes this by analyzing millions of documents that are already translated from one language to another and then looking for the common patterns and basic vocabulary of the language. After that, it picks the most accurate translation possible based on educated guesses that mostly turn out to be correct.
For now, all languages are updated monthly so that the ML system is up to date on new slangs and sayings!
We see the posts of our friends, family members in our newsfeed at the top and when we scroll down we see the posts related to our interests, and then we will see the trending posts on Facebook which have a lot of likes and comments.
Facebook News Feed according to a complex system of ranking that is managed by a Machine Learning algorithm.
The rank of anything that appears in your News Feed is decided on three factors. Your friends, family, public figures,or businesses that you interact with a lot are given top priority. Your feed is also customized according to the type of content you like (Movies, Books, Fashion, Video games, etc.) Also, posts that are quite popular on Facebook with lots of likes, comments,and shares have a higher chance of appearing on your Facebook News Feed.
- Textual Analysis
There is a lot of text on Facebook!!! To understand and manage this text in the correct manner, Facebook uses Deep Text which is a text engine based on deep learning that can understand thousands of posts in a second in more than 20 languages with as much accuracy as you can!
But understanding a language-based text is not that easy as you think! In order to truly understand the text, DeepText has to understand many things like grammar, idioms, slang words, context, etc.
DeepText uses Deep Learning and therefore it handles labeled data much more efficiently than traditional Natural Language Processing models.