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Using Microsoft AI to Build a Lung-Disease Prediction Model Using Chest X-Ray Images
Artificial Intelligence (AI) has emerged as one of the most disruptive forces behind digital transformation that is revolutionizing the way we live and work. This applies to the field of healthcare and medicine too, where AI is accelerating change and empowering physicians to achieve more. At Microsoft, the Health Next project is looking at innovative approaches to fuse research, AI and industry expertise to enable a new wave of healthcare innovations. The Microsoft AI platform empowers every developer to innovate and accelerate the development of intelligent apps. AI-powered experiences augment human capabilities and transform how we live, work, and play – and have enormous potential in allowing us to lead healthier lives.
Pixel-Level Land Cover Classification Using the Geo AI Data Science Virtual Machine and Batch AI
Microsoft launched the Geo AI Data Science Virtual Machine (DSVM), an Azure VM type specially tailored to data scientists and analysts that manage geospatial data. Learn how Microsoft used Geo AI DSVM, Batch AI and Microsoft Cognitive Toolkit in the joint land cover mapping project with the Chesapeake Conservancy and ESRI.
Demystifying Docker for Data Scientists – A Docker Tutorial for Your Deep Learning Projects
Data scientists who have been hearing a lot about Docker must be wondering whether it is, in fact, the best thing ever since sliced bread. If you too are wondering what the fuss is all about, or how to leverage Docker in your data science work (especially for deep learning projects) you’re in the right place. In this post, I present a short tutorial on how Docker can give your deep learning projects a jump start. In the process you will learn the basics of how to interact with Docker containers and create custom Docker images for your AI workloads.