Kí ni itara Analysis? Ìtumọ̀ | AI Understanding

Itumọ

Iṣẹ-ṣiṣe NLP kan ti o ṣe ipinlẹ ohun ẹdun tabi ero inu ọrọ.

Awọn ofin ti o jọmọ

Ti a npè ni idanimọ Ẹda (NER)

Iṣẹ-ṣiṣe NLP kan ti o ṣe idanimọ awọn nkan bii eniyan, awọn aaye, awọn ọjọ, tabi awọn ajọ.

GbólóhùnPiece

Tokenizer ede-agnostic ti o kọ ẹkọ awọn ipin ọrọ-ọrọ taara lati ọrọ aise laisi pipin-tẹlẹ lori aaye funfun.

Eto asọye ti awọn ofin tabi awọn igbesẹ ti kọnputa tẹle lati yanju iṣoro kan tabi pari iṣẹ-ṣiṣe kan.

Iṣẹ-ṣiṣe nibiti awoṣe kan ti n fi igbewọle si ọkan tabi diẹ ẹ sii awọn ẹka ti a ti ni asọye.

Apẹrẹ awoṣe multimodal ti o kọ ẹkọ awọn aṣoju pinpin laarin ọrọ ati awọn aworan.

Aṣoju fekito nomba ti o gba itumo atunmọ ti ọrọ, awọn aworan, tabi data miiran.

Kọ ẹkọ diẹ sii ninu awọn itọsọna ọfẹ wa

Sentiment Analysis AI in Satellite Imagery Analysis AI in Patent Search and Analysis AI in Telescope and Astronomical Image Analysis

Wo tun

Self-Supervised Learning Small Language Model (SLM)Semantic Search Sparse Model Scaling Law Supervised Learning Safety Filter Synthetic Data

Ṣawakiri ni kikun AI Gilosari Ṣawari gbogbo awọn itọsọna AI ọfẹ