Enterprises today are transforming their businesses using Machine Learning (ML) to develop a lasting competitive advantage. From healthcare to transportation, supply chain to risk management, machine learning is becoming pervasive across industries, disrupting markets and reshaping business models.
Organizations need the technology and tools required to build and deploy successful Machine Learning models and operate in an agile way. MLOps is the key to making machine learning projects successful at scale. What is MLOps ? It is the practice of collaboration between data science and IT teams designed to accelerate the entire machine lifecycle across model development, deployment, monitoring, and more. Microsoft Azure Machine Learning enables companies to fully embrace MLOps practices will and truly be able to realize the potential of AI in their business.
One great example of a customer transforming their business with Machine Learning and MLOps is TransLink. They support Metro Vancouver’s transportation network, serving 400 million total boarding’s from residents and visitors as of 2018. With an extensive bus system spanning 1,800 sq. kilometers, TransLink customers depend heavily on accurate bus departure times to plan their journeys.
To enhance customer experience, TransLink deployed 18,000 different sets of Machine Learning models to better predict bus departure
https://azure.microsoft.com/blog/azure-machine-learning-ml-for-all-skill-levels/Enterprises today are adopting artificial intelligence (AI) at a rapid pace to stay ahead of their competition, deliver innovation, improve customer experiences, and grow revenue. AI and machine learning applications are ushering in a new era of transformation across industries READ MORE
https://azure.microsoft.com/blog/automated-machine-learning-and-mlops-with-azure-machine-learning/Azure Machine Learning is the center for all things machine learning on Azure, be it creating new models, deploying models, managing a model repository, or automating the entire CI/CD pipeline for machine learning. We recently made some amazing announcements on READ MORE
This post is co-authored by Rangan Majumder, Group Program Manager, Bing and Maxim Lukiyanovm, Principal Program Manager, Azure Machine Learning.
Today we are announcing the open sourcing of our recipe to pre-train BERT (Bidirectional Encoder Representations from Transformers) built by the Bing team, including code that works on Azure Machine Learning, so that customers can unlock the power of training custom versions of BERT-large models using their own data. This will enable developers and data scientists to build their own general-purpose language representation beyond BERT.
The area of natural language processing has seen an incredible amount of innovation over the past few years with one of the most recent being BERT. BERT, a language representation created by Google AI language research, made significant advancements in the ability to capture the intricacies of language and improved the state of the art for many natural language applications, such as text classification, extraction, and question answering. The creation of this new language representation enables developers and data scientists to use BERT as a stepping-stone to solve specialized language tasks and get much better results than when building natural language processing systems from scratch.
The broad applicability of BERT means that most developers
The next time you see your physician, consider the times you fill in a paper form. It may seem trivial, but the information could be crucial to making a better diagnosis. Now consider the other forms of healthcare data that permeate your life—and that of your doctor, nurses, and the clinicians working to keep patients thriving. Forms and diagnostic reports are just two examples. The volume of such information is staggering, yet fully utilizing this data is key to reducing healthcare costs, improving patient outcomes, and other healthcare priorities. Now, imagine if artificial intelligence (AI) can be used to help the situation.
The Azure platform offers a wealth of services for partners to enhance, extend, and build industry solutions. Here we describe how SyTrue, a Microsoft partner focusing on healthcare uses Azure to empower healthcare organizations to improve efficiency, reduce costs, and improve patient outcomes.
Billions of records
Valuable insights remain locked in unstructured medical records such as scanned documents in PDF format that, while human-readable, present a major obstacle to the automation and analytics required. Over four billion medical notes are created every year. The clinical and financial insights embodied within these records are needed by an average of