Sp

Spent 450hrs to bring my CV down to 1 page (ML, AI)

Hacker News

Spent 450hrs to bring my CV down to 1 page (ML, AI)

10 second version: Get 10000feet view of job descriptions - https://be-distinguished.com 2 minute version : Hi HN, Long time lurker, big fan, and first time poster inspired by how this community elaborates on ideas and new products. Recently was given feedback that my CV was too long at 2 pages, I was at loss as to how to update it without having a high-level view of the requirements of the type of jobs I would be interested in. So I built https://be-distinguished.com to help me study relevant job requirements categorized by seniority, salary and keywords. I then used my site to update my own CV! Overall the whole process was far simpler than I thought it'd be and the work looked like below: [0]. study corpus (70hrs), [1]. gather job descriptions(requests - 50hrs), [2]. apply NLP to this text (nltk - 120hrs), [3]. have a custom spacy model to decide if a sentence is requirement (40hrs) [4]. return the results in a harmonized format (pandas - 50hrs), [5]. present findings through a website (flask/postgres/heroku/bootstrap - 120hrs). Have a look and let me know what you think. HN Special: I don't want to hoard this data and let it sit on some database. If it inspires, send across queries (sql or otherwise) you would like to run against this database. I would love to add them to a future version of BDDB. you can assume these columns for your mock queries: requirements, location, seniority, title, date, salary, keywords. relay email account for queries 8fi1pj5fb_at_mozmail_dot_com upwards and onwards!

Share card

Actual performance

32points
11comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: model, new, email · Missing: mac, agents, macos
51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released
50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

My
My CV Page, Built with VueJs43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My CV Page, Built with VueJs

Hacker News1
Cvmatch
Cvmatch21%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Your CV, Perfected by AI.

Product Hunt+11
MammansCV
MammansCV41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Professionell CV hjälp med AI

TrustMRRSaaS
My
My CV is also a bootloader37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My CV is also a bootloader

Hacker News255
Brillian Cahaya Sukses
Brillian Cahaya Sukses34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

CV Brillian Cahaya Sukses

Indie Hackers
Ch
Chatbot to find AI /ML courses using CV29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Chatbot to find AI /ML courses using CV

Hacker News1
Br
Bring your own Data: automatic ML (side project)53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Bring your own Data: automatic ML (side project)

Hacker News2
Sh
Show HN : startup failed, here's source (CV/ML for demographic analysis)47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Show HN : startup failed, here's source (CV/ML for demographic analysis)

Hacker News2
An
An annotation tool for ML and NLP63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

An annotation tool for ML and NLP

Hacker News76
An
An annotation tool for ML and NLP63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

An annotation tool for ML and NLP

Hacker News5