Announcing Data Science Utilities Version 0.11, for the Team Data Science Process

This post is authored by Hang Zhang, Senior Data Scientist Manager, Gopi Kumar, Principal Program Manager, and Xibin Gao, Data Scientist, at Microsoft. Back in September 2016, we released an early public preview of Team Data Science Process (TDSP), with the goal of supporting secure collaboration within enterprise data science organizations, with capabilities such as…


Qualification

Data Science and machine learning are very cool just now and It’s relatively easy to find lots of resources to learn either from books to MOOCs (massively Open Online Courses). But how can you prove you are an expert?  The Microsoft tradition and one that I have followed in the past is to get certified…


Add Intelligence to Any SQL App, with the Power of Deep Learning

Re-posted from the SQL Server blog. Recent results and applications involving Deep Learning have proven to be incredibly promising, and across a diverse set of areas too, including speech recognition, language understanding, computer vision and more. Deep Learning is changing customer expectations and experiences around a variety of products and mobile apps, whether we’re aware…


Moving eBird to the Azure Cloud

Re-posted from the Azure Data Lake & HDInsight blog. Hosted by the Cornell Lab of Ornithology, eBird is a citizen science project that allows birders to submit observations to a central database. Birders seek to identify and record the birds that they discover, and can also report how much effort it took to find those…


Hello 2017, and Recap of Top 10 Posts of 2016

As we kick off what will surely be another very exciting year of progress in artificial intelligence, machine learning and data science, we start with a quick recap of our “Top 10” most popular posts (based on aggregate readership) from the year just concluded. Here are the posts that had the most page views in…


Anomaly Detection: Models Ensemble

In the final article of their three-part series, SoftServe’s Data Science Group (DSG) wraps up their look at informational security risk identification by detecting deviations from the typical pattern of network activity.


Singapore Machine Learning & Data Science Summit – Recap

This post is authored by Tamarai G V, Senior Product Marketing Manager at Microsoft. Singapore has started to embrace the many benefits of digital transformation, and data plays a central role in this process. From using non-traditional indicators such as electricity consumption and public transportation to monitor the economy to helping the government improve the…


Exploring Azure Data with Apache Drill, Now Pre-Installed on the Data Science Virtual Machine

This post is authored by Gopi Kumar, Principal Program Manager in Microsoft’s Data Group. We recently came across Apache Drill, a very interesting data analytics tool. The introduction page to Drill describes it well: “Drill is an Apache open-source SQL query engine for Big Data exploration. Drill is designed from the ground up to support…


Three Models for Anomaly Detection: Pros and Cons

Continuing the previous research on Machine Learning: Achieving Ultimate Intelligence, SoftServe’s Data Science Group (DSG) describes informational security risk identification by detecting deviations from the typical pattern of network activity.


Building Intelligent Bots for Business

This post is authored by Herain Oberoi, Senior Director of Product Marketing at Microsoft. Earlier today, in San Francisco, we provided an update on how Microsoft is helping to democratize Artificial Intelligence (AI) by making it accessible to everyone and every organization. Today’s focus was on conversational computing, which combines the power of natural language…