Official Technical Resources: Microsoft (page 20)
Official Technical Resources · Microsoft: 312 entries in total; this page lists entries 286–300.
Precise answering
Understand Precise answering feature available in custom question answering.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Agent · Agent Frameworks
Link last checked: 2026-09-24
Custom question answering project lifecycle
Custom question answering learns best in an iterative cycle of model changes, utterance examples, deployment, and gathering data from endpoint queries.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: AI Agent · Agent Frameworks
Link last checked: 2026-09-24
Assertion detection
Learn about assertion detection.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Supervised Learning · Privacy and Data Compliance
Link last checked: 2026-09-24
Utilizing Fast Healthcare Interoperability Resources (FHIR) structuring in Text Analytics for Health
Learn about Fast Healthcare Interoperability Resources (FHIR) structuring
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Supervised Learning · Privacy and Data Compliance
Link last checked: 2026-09-24
Supported Text Analytics for health entity categories
Learn about categories recognized by Text Analytics for health
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Supervised Learning · Privacy and Data Compliance
Link last checked: 2026-09-24
Relation extraction
Learn about relation extraction
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Supervised Learning · Privacy and Data Compliance
Link last checked: 2026-09-24
Audio concepts in Azure Speech in Foundry Tools
An overview of audio concepts in Azure Speech in Foundry Tools.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Speech Recognition and Synthesis · Multimodal Models
Link last checked: 2026-09-24
What is a BLEU score?
BLEU is a measurement of the differences between machine translation and human-created reference translations of the same source sentence.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Transformer · Supervised Learning
Link last checked: 2026-09-24
Custom Translator text translations
Use the Microsoft Translator Hub to build your own machine translation system using your preferred terminology and style.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Transformer · Supervised Learning
Link last checked: 2026-09-24
Custom Translator Data filtering
When you submit documents to be used for training a custom system, the documents undergo a series of processing and filtering steps.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Transformer · Supervised Learning
Link last checked: 2026-09-24
What is a Translator custom dictionary?
How to create an aligned document that specifies a list of phrases or sentences (and their translations) that you always want Microsoft Translator to translate the same way. Dictionaries are sometimes also called glossaries or term bases.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Transformer · Supervised Learning
Link last checked: 2026-09-24
Custom Translator training and modeling?
A model is the system, which provides translation for a specific language pair. The outcome of a successful training is a model. To train a model, three mutually exclusive data sets are required training dataset, tuning dataset, and testing dataset.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Transformer · Supervised Learning
Link last checked: 2026-09-24
What are Custom Translator parallel documents?
Parallel documents are paired documents where one is the translation of the other. One document in the pair contains sentences in the source language and the other document contains these sentences translated into the target language.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Transformer · Supervised Learning
Link last checked: 2026-09-24
Sentence pairing and alignment in parallel documents
During the training execution, sentences present in parallel documents are paired or aligned. Custom Translator learns translations one sentence at a time, by reading a sentence and translating it. Then it aligns words and phrases in these two sentences to each other.
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Transformer · Supervised Learning
Link last checked: 2026-09-24
NotesOnThreading.md
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator - onnxruntime/docs/NotesOnThreading.md at main · microsoft/onnxruntime
Evidence use: For understanding, implementation, selection, reliability, security or migration decisions.
Limitations: Directly evidences only Microsoft's own implementation and claims. Recheck preview features and product lifecycle before use.
Related concepts: Model Deployment Options · LLM Inference Optimization
Link last checked: 2026-09-24