Adding multi-language support for Azure AI applications quickly
Thereis a growing demand for applications which support speech, language identification, translation or transliteration from one language to another. Common questions that customersencounteras they considerpossible solutionsare: How do we identify which language is being spoken/typed by the user? How dowetranslate one language to another for the user? Is there a way to transliterate text from one language to another? Canwedetermine the intent ofauser utterance? How do we incorporate natural language understanding intoourchatbot application for multiple languages? Complexproblems such as thesecannowbesolved using advancedAPIsthat are readily available without having to reinvent the wheel–no machine learning expertise required! This blogstarts off with a brief introductiontomachine translation andthen explores various topics like identifying thelanguageandhow to perform translation/transliteration ofspokenortyped textusing Microsoft’s Translator Text API.In addition,wealso discuss how translated or transliterated text can be integrated with LIUS.
Pre-train and Fine-tune Language Model with Hugging Face and Gaudi HPU.
In this blog, we provide a general guideline of pre-training and fine-tuning language models using Hugging Face. For illustration, we use pre-training language models for question generation (answer-agnostic) in Korean as running example.Reducing the distance to your Azure ML remote compute jobs
Under (hopefully) rare circumstances, after developing a training script and thorough local testing, it can still happen that the same script fails when executed on a remote AML compute target. Here, we are sharing some best practices around how to debug remote workloads on Azure ML.
Accelerating Azure Databricks Runtime for Machine Learning
Data Scientists love working in the Azure Databricks environment when developing their machine learning and artificial intelligence models. By simply installing Intel-optimized versions of scikit-learn and TensorFlow as described in this blog post, they can see potentially large performance gains that will save them time and money.
