Hold on Google TensorFlow, Facebook is coming with Visdom

Overview Visdom aims to facilitate visualization of (remote) data with an emphasis on supporting scientific experimentation. Broadcast visualizations of plots, images, and text for yourself and your collaborators. Organize your visualization space programmatically or through the UI to create dashboardsContinue reading… Hold on Google TensorFlow, Facebook is coming with Visdom

Building meaningful machine learning models for disease prediction

Dr Shirin Glander Setup All analyses are done in R using RStudio. For detailed session information including R version, operating system and package versions, see the sessionInfo() output at the end of this document. All figures are produced with ggplot2.Continue reading… Building meaningful machine learning models for disease prediction

5 Benefits of Data and Analytics for Positive Business Outcomes

Today, businesses can collect data along every point of the customer journey. This information might include mobile app usage, digital clicks, interactions on social media and more, all contributing to a data fingerprint that is completely unique to its owner.Continue reading… 5 Benefits of Data and Analytics for Positive Business Outcomes

Making data science accessible – Machine Learning – Tree Methods

What are Tree Methods?  Tree methods are commonly used in data science to understand patterns within data and to build predictive models. The term Tree Methods covers a variety of techniques with different levels of complexity but my aim isContinue reading… Making data science accessible – Machine Learning – Tree Methods

How a Japanese cucumber farmer is using deep learning and TensorFlow

It’s not hyperbole to say that use cases for machine learning and deep learning are only limited by our imaginations. About one year ago, a former embedded systems designer from the Japanese automobile industry named Makoto Koike started helping outContinue reading… How a Japanese cucumber farmer is using deep learning and TensorFlow