What is Feature Engineering? Definition | AI Understanding

Nkọwa

Ịmepụta ma ọ bụ gbanwee mgbanwe ntinye ka ọ dị mfe mmụta na ịdị irè karị.

Okwu ndị metụtara

Ngbanwe ntinye nke ihe nlere ji mee amụma.

Ọrụ ebe ihe nlere na-ekenye ntinye n'otu otu ma ọ bụ karịa akọwapụtara.

Prompt Engineering

Ịmepụta mkpali iji melite ogo mmepụta, ntụkwasị obi na njikwa.

Ụtụ isi n'usoro

Ọnụ ego agbakwunyere na oge, mgbakọ, ma ọ bụ ọsọ ngwaahịa achọrọ iji mee ka sistemu dị nchebe ma nwee ike ịchịkwa ya.

Mwepụta atụmatụ

Na-atụgharị data raw ka ọ bụrụ njirimara ozi nke ihe nlereanya nwere ike iji.

Ụlọ ahịa atụmatụ

Sistemụ jikwaa maka ịchekwa na ịnye njirimara ML akwadoro mgbe niile maka ọzụzụ na ntinye aka.

Mụtakwuo na ntuziaka efu anyị

Prompt Engineering Linear Probing and Frozen Feature Evaluation Feature Engineering Pipelines and Data Versioning Online and Offline Feature Serving Skew

Hụkwa

False Positive Few-Shot Learning False Negative Fine-Tuning Explainability Foundation Model Evaluation Set Function Calling

Chọgharịa akwụkwọ nkọwa AI zuru ezu Nyochaa ntuziaka AI niile efu