Felishelis

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Felishelis

Felishelis

@felisonhelison

Katılım Ocak 2023
524 Takip Edilen26 Takipçiler
Felishelis
Felishelis@felisonhelison·
@Hi_Mrinal No questions for now, I just want to tell you to keep posting interesting stuff. I keep saving them in my own knowledge base.
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Mrinal
Mrinal@Hi_Mrinal·
Let's do a Sunday AMA ... Will try to answer all of the questions
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Felishelis
Felishelis@felisonhelison·
@arpit_bhayani Perfect timing, Thanks for sharing this. I have an ongoing project and needed exactly this. Thank you very much.
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Arpit Bhayani
Arpit Bhayani@arpit_bhayani·
Today, I was going through a GitHub blog from 2017, and in it, they shared how they suggest topics for a repository. Here's how it works... The pipeline reads the repo name, description, and README, strips out noise like code blocks and file paths, then breaks the remaining text into candidate phrases by removing common stop words. The stopwords also contain GitHub-specific stop words like "push", "pull", and "tool" that appear in almost every repo and carry zero signal. These candidate words go through a logistic regression classifier trained on ~300 manually labeled examples of "good" and "bad" topics. Phrases like "running slowly" or "performing operations" get filtered out. The phrases are then scored using tf-idf, where each word's weight is computed against an IDF dictionary built from all public READMEs. This way, the word "application" scores lower than "assignment" because it shows up far more often across repos. Classic tf-idf. Finally, near-duplicate topics get collapsed. If "machine learning library" and "machine learning framework" both score high, the lower one gets dropped. This way, the final set is pretty crisp and varied. This pipeline does not have any heavy NLP or complex parsing - just simple, intuitive functions that just work :) It is actually a pretty breezy read as well.
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Felishelis
Felishelis@felisonhelison·
@steeltroops_ai Crazyyy, I'm checking this out and making my own implementation.
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𝙼𝚊𝚢 🌱
𝙼𝚊𝚢 🌱@steeltroops_ai·
i just built a full 𝗯𝗹𝗮𝗰𝗸 𝗵𝗼𝗹𝗲 𝗽𝗵𝘆𝘀𝗶𝗰𝘀 𝗲𝗻𝗴𝗶𝗻𝗲 in 𝗿𝘂𝘀𝘁. • real-time kerr metric integration • gpu-accelerated photon paths • built with 𝗥𝘂𝘀𝘁 + 𝗪𝗲𝗯𝗚𝗣𝗨 open source & live now: 🔗 blackhole-simulation.vercel.app
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Felishelis
Felishelis@felisonhelison·
@Hi_Mrinal This is like buying credibility. What were their repos like?
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Mrinal
Mrinal@Hi_Mrinal·
TIL if you get a big number of followers on github few startups would pay a big amount to just star or fork their repository got offered 4x of my twitter payout to star and fork their repository, I am still confused if I should go with it or not but a thought came across that if you build a genuine distribution there are endless ways to make income WOEWWW JUST WOEWW
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VG🌪️
VG🌪️@HelloVyom·
So @Docusign is on campus for juniors’ internships, and they’re paying ₹1.2 lakhs per month. Something TIER 69 students can only dream of. You didn't study during your JEE, now complain about all opportunities you'll miss. Now follow all bhaiya didi on X, youtube, linkedin and do MERN courses dreaming that your trash resume with TODO project will get selected by these companies 💀 While these students at good colleges will easily get these opportinities knocking at their door....
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Felishelis
Felishelis@felisonhelison·
@Hi_Mrinal Would appreciate on how to really get into tech twitter as a genuine person.
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Mrinal
Mrinal@Hi_Mrinal·
It's insane that if an individual decides to give 6 to 8 months to their social media presence posts genuine things without losing their essence or sanity, it could take them to places they have never imagined
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bhaskar
bhaskar@bhaskar__jha·
Congratulations @LandoNorris for maiden F1 title in Abu Dhabi Grand Prix 2025 🇮🇳🇮🇳🇮🇳
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Samanyu
Samanyu@sama__004·
🥀
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Felishelis
Felishelis@felisonhelison·
lil bro doesn't know 🥀
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bhaskar
bhaskar@bhaskar__jha·
Lando Norris's second half of the year lock-in needs to be studied. And oscar piastri's downfall 🤣😭
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bhaskar
bhaskar@bhaskar__jha·
Can anyone suggest me some really cool projects to make in golang
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Felishelis
Felishelis@felisonhelison·
@Hi_Mrinal I wish to learn more about it, can you link me some blogs / pages for the same you used as ref while building this?
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Mrinal
Mrinal@Hi_Mrinal·
Yoo, so I wrote a back pressure layer for tcp/udp streams. It adjusts the data flow rate between services based on both network conditions (something like RTT and packet loss). this layer can be useful to prevent sender overload, and cancel out buffer bloat
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Felishelis
Felishelis@felisonhelison·
@pranavthedev_ Congrats (but on off note, kinda hate apple ecosystem for making their stuff difficult to repair)
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Pranav Mailarpawar
Pranav Mailarpawar@pranvtwt·
And that’s how the Apple ecosystem gets completed :)
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mahak
mahak@noobcodervibes·
chronically online today, ignore my tweets pls
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jitesh💙
jitesh💙@Jitesh_117·
ig it's time I finally complete this project
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Felishelis
Felishelis@felisonhelison·
@neembu_paani31 dono ko saath mei bulaake rista decide karwa do. Diabolical situations create karna seekho lala : P
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tomato 🍅
tomato 🍅@neembu_paani31·
papa ne 2 ladkiyan dekh li mere liye 🥲 end is near guys. how to save myself
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Felishelis
Felishelis@felisonhelison·
@ten_on_tan Palthi maar ke baithna😊 Ngl feels much comfier. Bus woh pair thode sunn ho jaate baad mei.
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Tanisha
Tanisha@ten_on_tan·
economy seat and 5 feet.
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