Day one is error
Day two is the start of new habit
get back to your work!!
Day two is the start of new habit
get back to your work!!
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We all are Crystal palace today
aren't we?โบ๏ธ
aren't we?โบ๏ธ
๐3โค1
Omega Codes
We are funking champions ๐ let's go ๐ดโช๏ธ๐ดโช๏ธ๐ดโช๏ธ
What a birthday gift ๐
Thanks to be god
Thanks to be god
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Today was a productive day ๐ช
-I have built hybrid recommendation system task (I will share what I learned tomorrow)
-merge conflicts and test pr on project I'm a team lead
- and did one side hustle
-but still in have a lot of tasks to do this week๐ญ
But not only work i also been playing game (Valorant) with my friends ๐
I'm little tired and also I have to defend my task tomorrow so I'm head to bed early today
Good night ๐ด
-I have built hybrid recommendation system task (I will share what I learned tomorrow)
-merge conflicts and test pr on project I'm a team lead
- and did one side hustle
-but still in have a lot of tasks to do this week๐ญ
But not only work i also been playing game (Valorant) with my friends ๐
I'm little tired and also I have to defend my task tomorrow so I'm head to bed early today
Good night ๐ด
๐ฅ4โค1
Forwarded from Yohannes Haile (Yohannes Haile)
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Omega Codes
hybrid recommendation system
so lets start with What is recommendation system? ๐ค
A recommendation system is a system that suggests things users may like based on their interests, behavior, or similarities with other users.
You see them everywhere movies on Netflix, videos on YouTube, products on Amazon and songs on Spotify.
Main Types of Recommendation Systems:
โข Content-Based Filtering โ recommends items similar to what the user liked before
โข Collaborative Filtering โ recommends based on similar usersโ behavior
โข Hybrid Recommendation System โ combines multiple approaches for better recommendations
Recently, I built a Hybrid Recommendation System by combining:
Content-Based Filtering
Collaborative Filtering (SVD)
The goal was to improve recommendation accuracy by using both item similarity and user behavior together.
Still improving and experimenting with it
GitHub Repo: https://github.com/OmegaM97/hybrid-recommender
hope it was help full this is just simple summary if you want u can deep diveโบ๏ธ
A recommendation system is a system that suggests things users may like based on their interests, behavior, or similarities with other users.
You see them everywhere movies on Netflix, videos on YouTube, products on Amazon and songs on Spotify.
Main Types of Recommendation Systems:
โข Content-Based Filtering โ recommends items similar to what the user liked before
โข Collaborative Filtering โ recommends based on similar usersโ behavior
โข Hybrid Recommendation System โ combines multiple approaches for better recommendations
Recently, I built a Hybrid Recommendation System by combining:
Content-Based Filtering
Collaborative Filtering (SVD)
The goal was to improve recommendation accuracy by using both item similarity and user behavior together.
Still improving and experimenting with it
GitHub Repo: https://github.com/OmegaM97/hybrid-recommender
hope it was help full this is just simple summary if you want u can deep diveโบ๏ธ
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New feature โจ
So my friend suggest me to add Recommendation for EthioLink so users can get direct message from the bot based on their preferences, So I did
now on EthioLink bot you can customize your preferences and get only the jobs or opportunities you looking for ๐ and don't forget to add at least one value on one of the categories to get ur recommendations
check it out at: EthioLink bot
So my friend suggest me to add Recommendation for EthioLink so users can get direct message from the bot based on their preferences, So I did
now on EthioLink bot you can customize your preferences and get only the jobs or opportunities you looking for ๐ and don't forget to add at least one value on one of the categories to get ur recommendations
check it out at: EthioLink bot
โค3๐ฅ1