Ranking = Recommendation presented as a list.
In my article How do Recommendation Systems work? we learned different approaches to building recommendation systems. In this post, we’ll learn about stacking different models together to build an Ensemble Ranking Model.
What’s an Ensemble?
It’s a technique of combining multiple models in…
You want to learn about “Machine Learning”. You make a Google search. There are 10–15 results linking to the various sources of information. You open the links one by one. You take a one-shot look at them before deciding which ones among the lot you would invest time in reading…
The hatred towards Neymar is insane! We read all over the internet how much of a selfish player he is! People’s opinions are formed from the subjective treatment that Neymar receives from the media. But, what does the data say?
Who is a selfish player, really? For the sake of…
It’s just like how any of us learns.
There are 3 ways in which a machine learns:
Let’s say that we have a text file student_records.txt . Each line contains a student name and age. We want to parse student names and their ages.
Our first approach would be to read the files and store the values in a list/dictionary.
If I ask you to tell me one application of Machine Learning that you use everyday, what comes to your mind? No points for guessing! Recommendation engines are common in many products that you use daily, so much so that you do not even consciously think about it. Be it…