Worried about a shark attack when you go to the beach? Then you need to watch this video.

From causation and correlation, to relative and absolute risk, Jennifer Rogers explains how to figure out if the stats we are presented in newspapers are accurate.

Jennifer Rogers holds the position of Director of Statistical Consultancy Services at the University of Oxford having previously worked as a Post-Doctoral Research Fellow in the Department of Statistics funded by the National Institute of Health Research. She has a special interest in the development and application of novel statistical methodologies, particularly in medicine. Her main area of expertise is the analysis of recurrent events and her research has recently focused on developing and implementing appropriate methodology for the analysis of repeat hospitalisations in patients with heart failure but her research has many other applications in medicine such as epilepsy and cancer, but also in retail and engineering. She works alongside other statisticians, clinicians, computer scientists, industry experts and regulators.

In case you haven’t already noticed it, PowerPoint now includes AI technologies.

They help people create better presentations and become better presenters. Come see how AI helps make creating presentations quicker and easier with Designer and Presenter Coach.

In this video from Microsoft Research, learn how PowerPoint can listen to you practice and provide helpful tips for improvement.

Did you know that you can now train machine learning models with Azure ML once and deploy them in the Cloud (AKS/ACI) and on the edge (Azure IoT Edge) seamlessly thanks to ONNX Runtime inference engine.

In this new episode of the IoT Show, learn about the ONNX Runtime, the Microsoft built inference engine for ONNX models – its cross platform, cross training frameworks and op-par or better performance than existing inference engines.
From the description:
We will show how to train and containerize a machine learning model using Azure Machine Learning then deploy the trained model to a container service in the cloud and to an Azure IoT Edge device with IoT Edge across different HW platform – Intel, NVIDIA and Qualcomm.