Wo

Word Embedding: remaked word2vec in golang

Hacker News

Word Embedding: remaked word2vec in golang

Share card

Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
83%83% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
27%27% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
25%25% 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
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
12%12% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Ja
Japanese text8 corpus for word embedding43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Japanese text8 corpus for word embedding

Hacker News1
Wo
Word embedding playground (gensim and whatlies)43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Word embedding playground (gensim and whatlies)

Hacker News1
Em
Embedding visualizations for bloggers and journalists – VizFiddle52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Embedding visualizations for bloggers and journalists – VizFiddle

Hacker News1
Vi
Visualizing and Comparing Embedding Vectors as Heatmaps56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Visualizing and Comparing Embedding Vectors as Heatmaps

Hacker News3
Im
Implementing Embedding Gemma in PyTorch28%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Implementing Embedding Gemma in PyTorch

Hacker News3
Em
EmbedFlow –> Upgrade embedding models without re-embedding your corpus56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

EmbedFlow –> Upgrade embedding models without re-embedding your corpus

Hacker News6
I
I made a dataset for finetuning embedding models61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I made a dataset for finetuning embedding models

Hacker News1
Quaere
Quaere33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Embedding as a Service

Product Hunt+7
Bi
Binarized Attributed Network Embedding (ICDM 2018)50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Binarized Attributed Network Embedding (ICDM 2018)

Hacker News3
Bl
Blabr – Embedding scientific computation in your site41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Blabr – Embedding scientific computation in your site

Hacker News6