Highlights from the Connect(); conference

Connect();, the annual Microsoft developer conference, is wrapping up now in New York. The conference was the venue for a number of major announcements and talks. Here are some highlights related to data science, machine learning, and artificial intelligence: Lastly, I wanted to share this video presented at the conference from Stack Overflow. Keep an eye out for R community luminary David Robinson programming in R! You can find more from the Connect conference, including on-demand replays of the talks and keynotes, at the link below. Microsoft: Connect(); November 15-17, 2017
Original Post: Highlights from the Connect(); conference

Developing AI applications on Azure: learning plans at three levels

If you’re looking to expand your skills as an AI developer, or just getting started, these learning plans for AI Developers on Azure provide a wealth of information to get you up to speed. The beginner, intermediate and advanced tracks all provide step-by-step guides to setting up the tools and data in Azure, along with worked examples in iPython Notebooks. The Beginner AI Developer Learning Plan provides an introduction to artificial intelligence and cognitive systems. It begins with an overview of Cognitive Services, and then works through several examples of using those APIs in applications: handwriting comprehension, speech comprehension, and face detection. The Intermediate AI Developer Learning Plan walks through the process of creating an AI application that understands voice input. It begins with an overview of LUIS, the Language Understanding Intelligent Service, and walks through the process of defining intents, entities,…
Original Post: Developing AI applications on Azure: learning plans at three levels

Recap: EARL Boston 2017

By Emmanuel Awa, Francesca Lazzeri and Jaya Mathew, data scientists at Microsoft A few of us got to attend EARL conference in Boston last week which brought together a group of talented users of R from academia and industry. The conference highlighted various Enterprise Applications of R. Despite being a small conference, the quality of the talks were great and showcased various innovative ways in using some of the newer packages available for use in the R language. Some of the attendees were veteran R users while some were new comers to the R language, so there was a mix in the level of proficiency in using the R language.   R currently has a vibrant community of users and there are over 11,000 open source packages. The conference also encouraged women to join their local chapter for R Ladies…
Original Post: Recap: EARL Boston 2017

Microsoft R Open 3.4.2 now available

Microsoft R Open (MRO), Microsoft’s enhanced distribution of open source R, has been upgraded to version 3.4.2 and is now available for download for Windows, Mac, and Linux. This update upgrades the R language engine to the latest R 3.4.2 and updates the bundled packages.  MRO is 100% compatible with all R packages. MRO 3.4.2 points to a fixed CRAN snapshot taken on October 15 2017, and you can see some highlights of new packages released since the prior version of MRO on the Spotlights page. As always you can use the built-in checkpoint package to access packages from an earlier date (for compatibility) or a later date (to access new and updated packages). MRO 3.4.2 is based on R 3.4.2, a minor update to the R engine (you can see the detailed list of updates to R here). This update is backwards-compatible with…
Original Post: Microsoft R Open 3.4.2 now available

Two upcoming webinars

Two new Microsoft webinars are taking place over the next week that may be of interest: AI Development in Azure using Data Science Virtual Machines The Azure Data Science Virtual Machine (DSVM) provides a comprehensive development and production environment to Data Scientists and AI-savvy developers. DSVMs are specialized virtual machine images that have been curated, configured, tested and heavily used by Microsoft engineers and data scientists. DSVM is an integral part of the Microsoft AI Platform and is available for customers to use through the Microsoft Azure cloud. In this session, we will first introduce DSVM, familiarize attendees with the product, including our newest offering, namely Deep Learning Virtual Machines (DLVMs). That will be followed by technical deep-dives into samples of end-to-end AI development and deployment scenarios that involve deep learning. We will also cover scenarios involving cloud based scale-out and…
Original Post: Two upcoming webinars

Create editable Microsoft Office charts from R

R has a rich and infinitely flexible graphics system, and you can easily embed R graphics into Microsoft Office documents like PowerPoint or Word. The one thing I dread hearing after delivering such a document, though, is “how can I tweak that graphic?”. I could change the colors or fonts or dimensions in R, of course, but sometimes people just want to watch the world burn tweak graphics to their hearts’ content. If you’re in that situation, you have a couple of options for using R to create Office documents with graphics, and make those graphics editable. Both options work in conjunction with the “officer” package, which lets you create Word and PowerPoint documents from R.  The first option — the rvg package — lets you use traditional R graphics commands, but allows the PowerPoint or Word user to modify…
Original Post: Create editable Microsoft Office charts from R

Statistical Machine Learning with Microsoft ML

MicrosoftML is an R package for machine learning that works in tandem with the RevoScaleR package. (In order to use the MicrosoftML and RevoScaleR libraries, you need an installation of Microsoft Machine Learning Server or Microsoft R Client.) A great way to see what MicrosoftML can do is to take a look at the on-line book Machine Learning with the MicrosoftML Package Package by Ali Zaidi. The book includes worked examples on several topics: Exploratory data analysis and feature engineering Regression models Classification models for computer vision Convolutional neural networks for computer vision Natural language processing Transfer learning with pre-trained DNNs The book is part of Ali’s in-person workshop “Statistical Machine Learning with MicrosoftML”, and you can find further materials including data and scripts at this Github repository. If you’d like to experience the workshop in person, Ali will be presenting it…
Original Post: Statistical Machine Learning with Microsoft ML

Saving Snow Leopards with Artificial Intelligence

The snow leopard, the large cat native to the mountain ranges of Central and South Asia, is a highly endangered species. With an estimated estimated 3900-6500 individuals left in the wild, conservation efforts led by the Snow Leopard Trust are focused on preserving this iconic animal. But the snow leopard is an elusive creature: given their range and emote habitat (including the highlands of the Himalayas), they are difficult to study. In order to gather data about the creatures, researchers have used camera traps to capture more than 1 million images.  But not all of those images are of snow leopards. It’s a time-consuming process to classify those images as being of snow leopards, their prey, some other animal or nothing at all. To make things even more difficult, snow leopards have excellent camouflage, and can be difficult to spot even by…
Original Post: Saving Snow Leopards with Artificial Intelligence