Favorite Whether you are developing a machine learning (ML) model for reducing operating cost, improving efficiency, or improving customer satisfaction, there are no perfect solutions when it comes to producing an effective model. From an ML development perspective, data scientists typically go through stages of data exploration, feature engineering, model
Favorite Organizations are continuing to evaluate remote working arrangements and explore moving to a hybrid workforce model. Emerging trends suggest that not only has the number of online meetings attended by employees on a day-to-day basis increased, but also the number of attendees per meeting. One of the key challenges
Favorite The fields of natural language processing (NLP), natural language understanding (NLU), and related branches of machine learning (ML) for text analysis have rapidly evolved to address use cases involving text classification, summarization, translation, and more. State-of-the art, general-purpose architectures such as transformers are making this evolution possible. Looking at
Favorite Eastern Australia is among the most fire-prone regions in the world. Although bushfires are a regular occurrence in Australia, the 2019–2020 bushfire crisis set ablaze over 17 million hectares of land (larger than the size of England), costing the Australian economy more than $100 billion between property, infrastructure, social,
Favorite Machine learning (ML) and deep learning (DL) are becoming effective tools for solving diverse computing problems, from image classification in medical diagnosis, conversational AI in chatbots, to recommender systems in ecommerce. However, ML models that have specific latency or high throughput requirements can become prohibitively expensive to run at
Favorite In 2018 we began our flood forecasting initiative to help combat the catastrophic damage from floods each year by equipping those in harm’s way with accurate and detailed alerts. This work is a part of Google’s broader Crisis Response program which provides people access to trusted information and resources
Favorite For millions of people, being able to speak and be understood can be difficult as a result of conditions that can impact speech, including stroke, ALS, Cerebral Palsy, traumatic brain injury or Parkinson’s disease. Today, we’re inviting an initial group of people to test Project Relate, a new Android
Favorite Knowledge and information are part of a continuum but not the same, and knowledge problems cannot be solved with information tools alone. Image from wikimedia commons Often a client comes to us and says something like “We have a Knowledge Management problem. Our project teams can’t find the knowledge
Favorite Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra reimagines enterprise search for your websites and applications so your employees and customers can easily find the content they’re looking for, even when it’s scattered across multiple locations and content repositories within your organization. With
Favorite AutoGluon-Tabular is an open-source AutoML framework that requires only a single line of Python to train highly accurate machine learning (ML) models on an unprocessed tabular dataset. In this post, we walk you through a way of using AutoGluon-Tabular as a code-free AWS Marketplace product. We use this process
Shared by AWS Machine Learning November 11, 2021
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