Microsoft’s developments with R are designed to work with the entire R ecosystem rather than be distinct from it. This article contains an overview of what Microsoft has developed around the R ecosystem.

The Microsoft Python extension for Visual Studio code has been updated.

A demo containing sample code using Azure Search and Cognitive Services to provide insights and analysis around the JFK Files.

This blog post provides a summary of two real-world scenarios demonstrating how to use Azure Machine Learning alongside the Team Data Science Process (TDSP) to execute AI projects involving Natural Language Processing (NLP) use-cases, namely, for sentiment classification and entity extraction. Links to the GitHub code are provided.

A quick recap of three recent posts about Microsoft AI platform developments.

DecisionTreeExplorer - Simple Shiny App for visualizing simplicity/performance tradeoffs in decision trees.

2018-01-31 Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit version 2.4 released.

2018-02-08 Machine Learning for Apache Spark (MMLSpark) for Multi-GPU Distributed Training of Deep Networks version 0.11 released.

2018-02-16 Version 1.18 released. AirSim - Open source simulator based on Unreal Engine for autonomous vehicles from Microsoft AI & Research

This project presents a novel video dataset, named SLAC (Sparsely Labeled ACtions), for action recognition and localization. Links to the paper are in the YouTube video description.

A brief summary of the paper “Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions”. Links to the paper and an unofficial implementation are in the YouTube video description.

Part 1: Erika explains how to create deep learning models with music as the input. She begins by describing the problem of generating music by specifically describing how she generated the appropriate features from a midi file. She then describes the deep learning model she used in order to generate music.

Part 2: Erika follows up her previous episode by showing the actual code behind training and using the music generation model. This includes the code for both creating the features from the midi file and returning a midi file from the features. She also shows how Keras is used to generate the actual model.

A detailed discussion about the questions a practioneer would have when considering how they might use Microsoft SQL Server as the right tool for their production machine learning model deployments.

Podcast mentioned in first article. The Data Science Podcast Roger Peng and Hilary Parker talk about the latest in data science and data analysis in academia and industry. Co-hosts: Roger Peng of the Johns Hopkins Bloomberg School of Public Health and Hilary Parker of Stitch Fix.

An example of application modernization practice centered around data-driven intelligent apps (using SQL Server 2016 and Azure Database Services), and re-architect on-premises ISV/SaaS apps to Azure for scale.

A free book on Artificial Intelligence and its role in society. 🤓

“The spreadsheet software Microsoft Excel, when used with default settings, is known to convert gene names to dates and floating-point numbers. A programmatic scan of leading genomics journals reveals that approximately one-fifth of papers with supplementary Excel gene lists contain erroneous gene name conversions.”