Amazon’s SageMaker Object2Vec, a highly customizable algorithm that can learn embeddings of various types high-dimensional objects.
Link: https://aws.amazon.com/ru/blogs/machine-learning/introduction-to-amazon-sagemaker-object2vec/
#Object2Vec #Amazon #Embeddings
Link: https://aws.amazon.com/ru/blogs/machine-learning/introduction-to-amazon-sagemaker-object2vec/
#Object2Vec #Amazon #Embeddings
🎓Amazon have released its Free Machine Learning #course.
Course consits of 30+ digital ML classes totaling 45+ hours, aiming for improving skills of different roles: from Data Platform Engineer to Business Decision Maker.
Link: https://aws.amazon.com/ru/training/learning-paths/machine-learning/
#Amazon #ML #MOOC
Course consits of 30+ digital ML classes totaling 45+ hours, aiming for improving skills of different roles: from Data Platform Engineer to Business Decision Maker.
Link: https://aws.amazon.com/ru/training/learning-paths/machine-learning/
#Amazon #ML #MOOC
Amazon
Машинное обучение (ML) и искусственный интеллект (AI) – онлайн-курсы и очное обучение AWS
Развивайте навыки по работе с технологиями машинного обучения с помощью онлайн-курсов, аудиторных занятий и программ сертификации, предназначенных для специализированных ролей в области машинного обучения. Подробнее
Dynamic Transfer Learning for Named Entity Recognition
Paper with direct healthcare application by #Amazon interesting proposal to use Dynamic Transfer Network for architecture search
Link: https://arxiv.org/pdf/1812.05288.pdf
#healthcare #NLP
Paper with direct healthcare application by #Amazon interesting proposal to use Dynamic Transfer Network for architecture search
Link: https://arxiv.org/pdf/1812.05288.pdf
#healthcare #NLP
Racial Disparities in Automated Speech Recognition
To no surprise, speech recognition tools have #bias due to the lack of diversity in the datasets. Group of explorers addressed that issue and provided their’s research results as a paper and #reproducible research repo.
Project link: https://fairspeech.stanford.edu
Paper: https://www.pnas.org/cgi/doi/10.1073/pnas.1915768117
Github: https://github.com/stanford-policylab/asr-disparities
#speechrecognition #voice #audiolearning #dl #microsoft #google #apple #ibm #amazon
To no surprise, speech recognition tools have #bias due to the lack of diversity in the datasets. Group of explorers addressed that issue and provided their’s research results as a paper and #reproducible research repo.
Project link: https://fairspeech.stanford.edu
Paper: https://www.pnas.org/cgi/doi/10.1073/pnas.1915768117
Github: https://github.com/stanford-policylab/asr-disparities
#speechrecognition #voice #audiolearning #dl #microsoft #google #apple #ibm #amazon
