sdimi/average-word2vec
🔤 Calculate average word embeddings (word2vec) from documents for transfer learning
Jupyter Notebook
Stargazers
- AndyFouAristotle University of Thessaloniki
- BartMiki@deepsense.ai
- bastienbot@onboardiq
- CardiffKT
- etakdcMéxico D.F
- eugenewareClickVideo
- eyadsibai
- Fazel94Maktabkhooneh.org
- GeorgeMcIntireBerkeley
- gopi3e
- guillaume-chevalier@Neuraxio
- hailiang-wang@Chatopera
- jdphilius
- jennychiou
- jurebb@photomath
- lodziajelembasy
- martinnormark@LEGO
- misanthropistZZY
- mvujk
- mzhang13
- nickcastro
- NISH1001@NASA-IMPACT
- olgasilyutina
- parvathysaratGeorgia Tech
- passalisAristotle University of Thessaloniki
- pjnani12Hyundai Mobis
- PolichinelPRIO
- rayush7Paris
- samkugjiKorea, Canada
- sigma23
- sleter@deepsense-ai
- tnlinAlibaba Tongyi
- trisongzGrowth Engine AI
- tuananhhedspibk@air-closet
- Vinod-Kumar-GHyderabad, India
- VuThuHien